Publications

Additional bibliographic information can be found at DBLP ID: 92/309-1 (don't know how to curate this list).

Semantic Scholar ID: 38746648 (don't know how to add/delete)

Download some papers via ACM Digital Library; ORCID: 0000-0002-3264-7904

Google Scholar Profile ID: Dzf46C8AAAAJ (regularly curated).

International Conferences

Conference Patent Journal Workshop Book

  • Garima Agrawal, Tharindu Sandaruwan Kumarage, Zeyad Alghamdi, and Huan Liu. ``Can Knowledge Graphs Reduce Hallucinations in LLMs? : A Survey", Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2024). June 16-21, 2024, Mexico City, Mexico.
  • Ujun Jeong, Paras Sheth, Anique Tahir, Faisal Alatawi, H Russell Bernard, and Huan Liu. ``Exploring Platform Migration Patterns between Twitter and Mastodon: A User Behavior Study", In International AAAI Conference on Web and Social Media (ICWSM2024), June 3-6, 2024. Buffalo, New York. arxiv
  • Zeyad Alghamdi, Tharindu Kumarage, Garima Agrawal, and Huan Liu. ``Less is More: Stress Detection through Condensed Social Media Contents", In 11th European Conference on Social Media (ECSM), 30 - 31 May 2024, University of Brighton, UK
  • Raha Moraffah, Shubh Khandelwal, Amrita Bhattacharjee, and Huan Liu.  ``Adversarial Text Purification: A Large Language Model Approach for Defense", In the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, (PAKDD), May 7-10, 2024, Taipei, Taiwan.
  • Zhen Tan, Lu Cheng, Song Wang, Bo Yuan, Jundong Li, and Huan Liu. ``Interpreting Pretrained Language Models via Concept Bottlenecks'', In the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, (PAKDD), May 7-10, 2024, Taipei, Taiwan.
  • Raha Moraffah and Huan Liu. ``Exploiting Class Probabilities for Black-box Sentence-level Attacks”, In the 18th Conference of the European Chapter of the Association for Computational Linguistics (EACL),  March 17-22, 2024, St. Julians, in Malta.
  • Bohan Jiang, Zhen Tan, Ayushi Nirmal, and Huan Liu. ``Disinformation Detection: An Evolving Challenge in the Age of LLMs", SIAM International Conference on Data Mining (SDM24), April 18-20, 2024. Houston, TX.
  • Ujun Jeong, Ayushi Nirmal, Kritshekhar Jha, Xu Tang, H. Russell Bernard, and Huan Liu. ``User Migration across Multiple Social Media Platforms", SIAM International Conference on Data Mining (SDM24), April 18-20, 2024. Houston, TX.
  • Paras Sheth, Raha Moraffah, Tharindu S Kumarage, Aman Chadha, and Huan Liu. ``Causality Guided Disentanglement for Cross-Platform Hate Speech Detection",  The 17th  ACM International Conference on Web Search and Data Mining (WSDM2024), March 4-8, 2024. Merida, Yucatan, Mexico.
  • Zhen Tan, Tianlong Chen, Zhenyu Zhang, and Huan Liu. ``Sparsity-guided Holistic Explanation for LLMs with Interpretable Inference-time Intervention",  Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI2024), February 20-27, 2024. Vancouver, Canada.
  • Baoyu Jing, Yuchen Yan, Kaize Ding, Chanyoung Park, Yada Zhu, Huan Liu, and Hanghang Tong. ``Sterling: Synergistic Representation Learning on Bipartite Graphs", Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI2024), February 20-27, 2024. Vancouver, Canada.
  • Garima Agrawal, Kuntal Pal, Yuli Deng, Huan Liu and Ying-Chih Chen. ``CyberQ: Generating Questions and Answers for Cybersecurity Education using Knowledge Graph-Augmented LLMs", EAAI: The Symposium on Educational Advances in Artificial Intelligence (EAAI2024), Collocated with AAAI2024. Feburary 24-25, 2024. Vancouver, Canada.

2023

  • Tharindu Kumarage, Paras Sheth, Raha Moraffah, Joshua Garland, and Huan Liu. ``How Reliable Are AI-Generated-Text Detectors? An Assessment Framework Using Evasive Soft Prompts", Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), Singapore, Dec 6 -10, 2023.
  • Faisal Alatawi, Paras Sheth and Huan Liu. ``Quantifying the Echo Chamber Effect: an Embedding Distance-based Approach",  The IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM2023), Nov 6-9, 2023. Kusadasi, Turkey.
  • Tharindu Kumarage and Huan Liu. ``Neural Authorship Attribution: Stylometric Analysis on Large Language Models", CyberC, IEEE TCCC, Jiangsu, China November 2 - 4, 2023.
  • Amrita Bhattacharjee, Tharindu Kumarage, Raha Moraffah, and Huan Liu. ``ConDA: Contrastive Domain Adaptation for AI-generated Text Detection", The 13th International Joint Conference NLP and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (IJCNLP-AACL).   Nov 1 -4, 2023. Bali, Indonesia. Outstanding Paper Award
  • Tharindu Kumarage, Amrita Bhattacharjee, Djordje Padejski, Kristy Roschke, Dan Gillmor,  Scott Ruston, Huan Liu, and Joshua Garland. ``J-Guard: Journalism Guided Adversarially Robust Detection of AI-generated News", The 13th International Joint Conference NLP and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (IJCNLP-AACL).   Nov 1 -4, 2023. Bali, Indonesia.
  • Anique Tahir, Lu Cheng, and Huan Liu. ``Fairness through Aleatoric Uncertainty", 32nd ACM International Conference on Information and Knowledge Management  (CIKM2023), October 21 - 25, 2023. Birmingham, UK.
  • Paras Sheth, Ahmadreza David Mosallanezhad, Kaize Ding, Reepal Shah, John Sabo, Huan Liu and K. Selçuk Candan. ``STREAMS: Towards Spatio-Temporal Causal Discovery with Reinforcement Learning for Streamflow Rate Prediction", Applied Research track. 32nd ACM International Conference on Information and Knowledge Management  (CIKM2023), October 21 - 25, 2023. Birmingham, UK.
  • Zhen Yang, Junrui Liu, Tong Li, Di Wu, Shiqiu Yang and Huan Liu, ``A two-tier shared embedding method for review-based recommender systems", 32nd ACM International Conference on Information and Knowledge Management  (CIKM2023), October 21 - 25, 2023. Birmingham, UK.
  • Qinghai Zhou, Kaize Ding, Huan Liu, and Hanghang Tong. ``Learning Node Abnormality with Weak Supervision", 32nd ACM International Conference on Information and Knowledge Management  (CIKM2023), October 21 - 25, 2023. Birmingham, UK.
  • Hirthik Mathavan, Zhen Tan, Nivedh Mudiam and Huan Liu. ``Inductive Linear Probing for Few-shot Node Classification", 16th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS2023), September 22-23, 2023. Pittsburgh, PA.
  • Suraj Jyothi Unni, Paras Sheth, Kaize Ding, Huan Liu and K. Selcuk Candan. ``UPREVE: An End-to-End Causal Discovery Benchmarking System", Demo Track, 16th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS2023), September 22-23, 2023. Pittsburgh, PA.
  •  Ayushi Nirmal, Bohan Jiang, and Huan Liu. ``SocioHub: An Interactive Tool for Cross-Platform Social Media Data Collection", Demo Track, 16th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS2023), September 22-23, 2023. Pittsburgh, PA.
  • Paras Sheth, Tharindu Kumarage, Raha Moraffah, Aman Chadha, and Huan Liu. ``PEACE: Cross-Platform Hate Speech Detection-A Causality-guided Framework",  European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD2023), September 18-22, 2023. Torino, Italy.
  • Zhen Tan, Ruocheng Guo, Kaize Ding, and Huan Liu. ``Virtual Node Tuning for Few-Shot Node Classification", ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD2023), August 6 - 10, 2023. Long Beach, CA.
  • Song Wang, Zhen Tan, Huan Liu, Jundong Li. ``Contrastive Meta-Learning for Few-shot Node Classification", ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD2023), August 6 - 10, 2023. Long Beach, CA.
  • Yixin Liu, Kaize Ding, Jianling Wang, Vincent Lee, Huan Liu, and Shirui Pan. ``Learning Strong Graph Neural Networks with Weak Information", ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD2023), August 6 - 10, 2023. Long Beach, CA.
  • Kaize Ding, Albert Jiongqian Liang, Bryan Perozzi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed H. Chi, Huan Liu and Derek Zhiyuan Cheng. ``HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraphs", the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval. short paper, July 23-27, 2023. Taipei, Taiwan. 
  • Zeyad Alghamdi,Tharindu Kumarage, Mansooreh Karami, Faisal Alatawi, Ahmadreza Mosallanezhad, Huan Liu. ``Studying the Influence of Toxicity and Emotion Features for Stress Detection on Social Media", Proceedings of the 10th European Conference on Social Media (ECSM2023), May 18-19, 2023. Krakow, Poland.
  • Yixin Liu*, Kaize Ding*, Huan Liu, and Shirui Pan. ``GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection",  16th ACM International Conference on Web Search and Data Mining (WSDM). Feb. 27 - Mar 3, 2023. Singapore
  • Kaize Ding*, Yancheng Wang*, Yingzhen Yang, and Huan Liu. ``Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning", 37th AAAI Conference on Artificial Intelligence (AAAI). Feb. 7 - 14, 2023. D.C.

2022

  • Ujun Jeong, Kaize Ding, Lu Cheng, Ruocheng Guo, Kai Shu, and Huan Liu. ``Nothing Stands Alone: Leveraging News Relations through a Hypergraph for Fake News Detection", IEEE International Conference on Big Data (BigData), Dec. 17 - 20, 2022, Osaka, Japan.
  • Raha Moraffah, Paras Sheth, and Huan Liu. ``Exploring the Target Distribution for Surrogate-Based Black-Box Attacks", Short Paper, IEEE International Conference on Big Data (BigData), Dec. 17 - 20, 2022, Osaka, Japan.
  • Zhen Tan*, Song Wang*, Kaize Ding*, Jundong Li and Huan Liu. ``Transductive Linear Probing: A Novel Framework for Few-shot Node Classification", 1st Learning on Graphs Conference (LoG), virtual, Dec. 9-12, 2022.
  • Raha Moraffah and Huan Liu. ``Query-Efficient Target-Agnostic Black-Box Attack", IEEE 22nd International Conference on Data Mining (ICDM22), Nov. 28 - Dec. 1, 2022, Orlando, FL.
  • Zhe Xu, Kaize Ding, Yu-Xiong Wang, Huan Liu, and Hanghang Tong. ``Generalized Few-Shot Node Classification", IEEE 22nd International Conference on Data Mining (ICDM22), Nov. 28 - Dec. 1, 2022, Orlando, FL.
  • Lu Cheng, Nayoung Kim, and Huan Liu. ``Debiasing Word Embeddings with Nonlinear Geometry", In Proceedings of the 29th International Conference on Computational Linguistics (COLING2022), October 12-17, 2022.  Gyeongju, Republic of Korea.
  • Paras Sheth, Ruocheng Guo, Kaize Ding, Lu Cheng, K. Selcuk Candan, and Huan Liu. "Causal Disentanglement with Network Information for Debiased Recommendations", Short Paper, the 15th International Conference on Similarity Search and Applications (SISAP), Oct 5-7, 2022. Bologna, Italy.
  • Zhen Tan, Kaize Ding, Ruocheng Guo, and Huan Liu. ``Supervised Graph Contrastive Learning for Few-shot Node Classification", In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML-PKDD2022), Sept. 19-23, 2022. Grenoble, France.
  • Mansooreh Karami, Ahmadreza David Mosallanezhad, Michelle Mancenido, and Huan Liu. ```Let's Eat Grandma": Does Punctuation Matter in Sentence Representation?',  In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML-PKDD2022), Sept. 19-23, 2022. Grenoble, France.
  • Mansooreh Karami, Ahmadreza Mosallanezhad, Paras Sheth and Huan Liu. ``Estimating Topic Exposure for Under-Represented Users on Social Media", In Proceedings of 15th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS2022). September 20-23, 2022. Pittsburg, PA.
  • Raha Moraffah, Suraj Jyothi Unni, Adrienne Raglin and Huan Liu ``Causal Data Fusion for Multi-modal Disaster Classification in Social Media", In Proceedings of 15th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS2022). September 20-23, 2022. Pittsburg, PA.
  • Bohan Jiang, Paras Sheth, Baoxin Li and Huan Liu. ``CoVaxNet: An Online-Offline Data Repository for COVID-19 Vaccine Hesitancy Research", In Proceedings of 15th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS2022). September 20-23, 2022. Pittsburg, PA.
  • Nayoung Kim, Ahmadreza Mosallanezhad, Lu Cheng, Baoxin Li and Huan Liu. ``Bridge the Gap: the Commonality and Differences Between Online and Offline COVID-19 Data", In Proceedings of 15th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS2022). September 20-23, 2022. Pittsburg, PA.
  • Anique Tahir, Lu Cheng, Paras Sheth and Huan Liu. ``Improving Vaccine Stance Detection by Combining Online and Offline Data", In Proceedings of 15th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS2022). September 20-23, 2022. Pittsburg, PA.
  • Ujun Jeong, Zeyad Alghamd, Kaize Ding, Lu Cheng, Baoxin Li and Huan Liu. ``Classifying COVID-19 related Meta Ads using Discourse Representation through Hypergraph",  In Proceedings of 15th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS2022). September 20-23, 2022. Pittsburg, PA.
  • Amrita Bhattacharjee*, Mansooreh Karami*, and Huan Liu. ``Text Transformations in Contrastive Self-Supervised Learning: A Review", In Proceedings of the 2022 International Joint Conferences on Artificial Intelligence (IJCAI-ECAI2022) Survey Track, July 23 - 29, 2022. Vienna, Austria.
  • Chuxu Zhang, Kaize Ding, Jundong Li, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla, Huan Liu. ``Few-Shot Learning on Graphs: A Survey", In Proceedings of the 2022 International Joint Conferences on Artificial Intelligence (IJCAI-ECAI2022) Survey Track, July 23 - 29, 2022. Vienna, Austria.
  • Lu Cheng, Ahmadreza (David) Mosallanezhad, Yasin Silva, Deborah Hall and Huan Liu. ``Bias Mitigation for Toxicity Detection via Sequential Decisions", The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022), July 11-15, 2022. Madrid, Spain.
  • Lu Cheng, Ruocheng Guo, Kasim Selcuk Candan, and Huan Liu. ``Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication", 16th AAAI International Conference on Web and Social Media (ICWSDM 2022), June 6-9, 2022. Atlanta, Georgia and Online.
  • Xinyi Zhou, Kai Shu, Vir V. Phoha, Huan Liu and Reza Zafarani. ````This is Fake! Shared it by Mistake": Assessing the Intent of Fake News Spreaders", The ACM Web Conference 2022, the Web4Good Speical Track, April 25-29, 2022, Lyon, France and online
  • Ahmadreza (David) Mosallanezhad, Mansooreh Karami, Kai Shu, Michelle Mancenido and Huan Liu. ``Domain Adaptive Fake News Detection via Reinforcement Learning", The ACM Web Conference 2022, the Web4Good Speical Track, April 25-29, 2022, Lyon, France and online
  • Zhen Tan, Kaize Ding, Ruocheng Guo and Huan Liu. ``Graph Few-shot Class-incremental Learning", 15th ACM International Conference on Web Search and Data Mining (WSDM 2022), February 27 - March 3, 2022. Tempe, Arizona
  • Lu Cheng, Ruocheng Guo, and Huan Liu. ``Causal Mediation Analysis with Hidden Confounders", 15th ACM International Conference on Web Search and Data Mining (WSDM 2022), February 27 - March 3, 2022. Tempe, Arizona
  • Lu Cheng, Ruocheng Guo, and Huan Liu. ``Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies", 15th ACM International Conference on Web Search and Data Mining (WSDM 2022), Feb 27 - March 3, 2022. Tempe, Arizona
  • Kaize Ding, Jianling Wang, James Caverlee, and Huan Liu. ``Meta Propagation Networks for Few-shot Semi-supervised Learning on Graphs", 36th AAAI Conference on Artificial Intelligence (AAAI-22), February 22 - March 1, 2022. Vancouver, BC, Canada

2021

  • Ahmadreza (David) Mosallanezhad, Kai Shu, and Huan Liu. ``Generating Topic-Preserving Synthetic News", IEEE International Conference on Big Data, online, Dec 15-18, 2021.
  • Kaize Ding, Dingcheng Li, Alexander Hanbo Li, Xing Fan, Chenlei Guo, Yang Liu, and Huan Liu. ``Learning to Selectively Learn for Weakly-supervised Paraphrase Generation", The Conference on Empirical Methods in Natural Language Processing (EMNLP), November 7-11, 2021. Punta Cana, Dominican Republic
  • Kaize Ding, Xuan Shan, and Huan Liu. ``Towards Anomaly-resistant Graph Neural Networks via Reinforcement Learning", Short, In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM2021), November 1-5, 2021. Online, Queensland, Australia [335]
  • Paras Sheth, Ujun Jeong, Ruocheng Guo, Huan Liu, and K. Selcuk Candan.``CauseBox: A Causal Inference Toolbox for Benchmarking Treatment Effect Estimators with Machine Learning Methods" Demo, In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM2021), November 1-5, 2021. Online, Queensland, Australia
  • Mansooreh Karami, Tahora H. Nazer, and Huan Liu (2021). "Profiling Fake News Spreaders on Social Media through Psychological and Motivational Factors", In Proceedings of the 32nd ACM Conference on Hypertext and Social Media (HT'21), August 30 - September 2, 2021, Dublin, Ireland.
  • Lu Cheng, Ahmadreza Mosallanezhad*, Paras Sheth*, and Huan Liu. ``Causal Learning for Socially Responsible AI", In Proceedings of the 2021 International Joint Conferences on Artificial Intelligence (IJCAI2021), Survey Track, August 21-26, Montreal, Canada.
  • Xueying Zhan, Huan Liu, Qing Li, Antoni B. Chan. ``A Comparative Survey: Benchmarking for Pool-based Active Learning", In Proceedings of the 2021 International Joint Conferences on Artificial Intelligence (IJCAI2021), Survey Track, August 21-26, Montreal, Canada.
  • Lu Cheng, Ruocheng Guo, Kai Shu, and Huan Liu. ``Causal Understanding of Fake News Dissemination on Social Media",  In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD2021). Online Virtual Event. August 14-18, 2021. [330]
  •  Lu Cheng*, Ahmadreza Mosallanezhad*, Yasin Silva, Deborah Hall, and Huan Liu. ``Mitigating Bias in Session-based Cyberbullying Detection: A Non-Compromising Approach",  In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics (ACL-IJCNLP2021), Bangkok, Thailand. August 1-6, 2021.
  • Walaa Alnasser, Ghazaleh Beigi and Huan Liu. ``Privacy Preserving Text Representation Learning Using BERT", International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS 2021), July 6 - 9, 2021. Online
  • Ujun Jeong, Kaize Ding, and Huan Liu. ``FBAdTracker: An Interactive Data Collection and Analysis Tool for Facebook Advertisements", International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS 2021), Demo Track, July 6 - 9, 2021. Online
  • Tharindu Kumarage, Amrita Bhattacharjee, Kai Shu, and Huan Liu. ``Data Generation for Neural Disinformation Detection ", International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS 2021), Working Paper Track,  July 6 - 9, 2021. Online
  • Bohan Jiang,Mansooreh Karami, Lu Cheng, Tyler Black and Huan Liu. ``Mechanisms and Attributes of Echo Chambers in Social Media", International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS 2021), Working Paper Track,  July 6 - 9, 2021. Online [325]
  • Kaize Ding, Qinghai Zhou, Hanghang Tong and Huan Liu. ``Few-shot Network Anomaly Detection with Cross-network Meta-learning". In Proceedings of the International Web Conference, Ljubljana, Slovenia. April 19-23, 2021.
  • Suyu Ge, Lu Cheng, and Huan Liu. ``Improving Cyberbullying Detection with User Interaction". In Proceedings of the 2021 International World Wide Web Conference, Ljubljana, Slovenia. April 19-23, 2021.
  • Kai Shu, Yichuan Li, Kaize Ding and Huan Liu. ``Fact-enhanced Synthetic News Generation". In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2021.
  • Lu Cheng, Ruocheng Guo, and Huan Liu. ``Long-Term Effect Estimation with Surrogate Representation”. The 14th ACM International Conference on Web Search and Data Mining (WSDM2021), March 8-12, 2021. Jerusalem, Israel.

2020

  • Lo Pang-Yun Ting, Shan-Yun Teng, Suhang Wang, Kun-Ta Chuang, and Huan Liu.``Learning Latent Perception Graphs for Personalized Unknowns Recommendation".  The Second IEEE International Conference on Cognitive Machine Intelligence (CogMI), Dec 1-3, 2020. Online [320]
  • Adrienne Raglin, Raha Moraffah and Huan Liu. ``Causality and Uncertainty of Information for Content Understanding". The Second IEEE International Conference on Cognitive Machine Intelligence (CogMI), Dec 1-3, 2020. Online
  • Kaize Ding, Jianling Wang, Jundong Li, Dingcheng Li and Huan Liu. “Be More with Less:Hypergraph Attention Networks for Inductive Text Classification”. The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), November 16 20, 2020. Online
  • Lu Cheng, Kai Shu, Siqi Wu, Yasin N. Silva, Deborah Hall, and Huan Liu. ``Unsupervised Cyberbullying Detection via Time-Informed Deep Clustering". In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM'20), Oct. 19-23, 2020, Online.
  • Kaize Ding,  Jianling Wang, Jundong Li, Kai Shu, Chenghao Liu, and Huan Liu. ``Graph Prototypical Networks for Few-shot Learning on Attributed Networks". In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM'20), Oct. 19-23, 2020, Online.
  • Kai Shu, Guoqing Zheng, Yichuan Li, Subhabrata Mukherjee, Ahmed Hassan Awadallah, Scott Ruston, and Huan Liu. ``Early Detection of Fake News with Multi-sourceWeak Social Supervision", Proceedings of The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2020). September 14 - 18, 2020, Ghent, Belgium. pdf, news report [315]
  • Qianru Wang, Bin Guo, Yi Ouyang, Kai Shu, Zhiwen Yu and Huan Liu. ``Spatial Community-Informed Evolving Graphs for Demand Prediction", Proceedings of The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2020). September 14 - 18, 2020, Ghent, Belgium. pdf
  • Ruocheng Guo, Xiaoting Zhao, Adam Henderson, Liangjie Hong and Huan Liu.``Debiasing Grid-based Product Search for E-commerce", In Proceedings of 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2020 ADS Track). August 23-27, 2020. San Diego, CA. pdf
  • Jianling Wang, Kaize Ding, Liangjie Hong, Huan Liu, and James Caverlee. ``Next-Item Recommendation with Sequential Hypergraphs", Proceedings of 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2020). July 25-30, 2020, Xi'an, China. pdf
  • Kaize Ding, Jundong Li, Nitin Agarwal, and Huan Liu. ``Inductive Anomaly Detection on Attributed Networks", IJCAI-PRICAI2020. new date January 2021, Japan. pdf
  • Ruocheng Guo, Jundong Li, Yichuan Li, K. Selçuk Candan, Adrienne Raglin,  and Huan Liu. ``IGNITE: A Minimax Game Toward Learning Individual Treatment Effects from Networked Observational Data", FinTech Track, IJCAI-PRICAI2020. pdf [310]
  • Kai Shu, Liangda Li, Suhang Wang, Yunhong Zhou, and Huan Liu. ``Joint Local and Global Sequence Modeling in Temporal Correlation Networks for Trending Topic Detection", Proceedings of 12th ACM Web Science Conference (WebSci2020). pdf
  • Kai Shu, Deepak Mahudeswaran, Suhang Wang, and Huan Liu. ``Hierarchical Propagation Networks for Fake News Detection: Investigation and Exploitation", AAAI International Conference on Web and Social Media (ICWSM), June 2020. Atlanta, Georgia. pdf
  • Lu Cheng, Ruocheng Guo, K. Selcuk Candan, and Huan Liu. ``Representation Learning for Imbalanced Cross-Domain Classification", SAM International Conference on Data Mining (SDM20), May 7-9, 2020. Cincinnati, Ohio. pdf
  • Ruocheng Guo, Jundong Li, and Huan Liu. ``Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data", SAM International Conference on Data Mining (SDM20), May 7-9, 2020. Cincinnati, Ohio. pdf
  • Lin Tian, Xiuzhen Zhang, Yan Wang, and Huan Liu. ``Early Detection of Rumours on Twitter via Stance Transfer Learning", European Conference on Information Retrieval, April 2020, pp 575 - 588. [305]
  • Lu Cheng, Jundong Li, K. Selcuk Candan, and Huan Liu. ``Tracking Disaster Footprints with Social Stream Data", In Proceedings of 34th AAAI Conference on Artificial Intelligence (AAAI-20), Feb. 07-12, 2020, New York, New York. pdf
  • Ghazaleh Beigi, Ahmadreza Mosallanezhad, Ruocheng Guo, Hamidreza Alvari, Alexander Nou and Huan Liu. ``Privacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning", The 13th ACM International Conference on Web Search and Data Mining (WSDM),  February 3-7, 2020. Houston, Texas. pdf
  • Ruocheng Guo, Jundong Li and Huan Liu. ``Learning Individual Causal Effects with Networked Observational Data", The 13th ACM International Conference on Web Search and Data Mining (WSDM),  February 3-7, 2020. Houston, Texas. pdf

2019

  • Adrienne J Raglin, Dijiang Huang, Huan Liu, James McCabe. ``Smart CCR IoT: Internet of Things Testbed", 2019 IEEE 5th International Conference on Collaboration and Internet Computing (CIC), pp 232-235, December 12, 2019, Los Angeles, CA.
  • Lu Cheng, Ruocheng Guo, Raha Moraffah, K.S. Candan, Adrienne Raglin, and Huan Liu. ``A Practical Data Repository for Causal Learning with Big Data", BenchCouncil International Symposium on Benchmarking, Measuring and Optimizing (BENCH19), November 14-16, 2019. Denver, Colorado. pdf
  • Yichuan Li, Ruocheng Guo, Weiying Wang and Huan Liu.``Causal Learning in Question Quality Improvement", BenchCouncil International Symposium on Benchmarking, Measuring and Optimizing (BENCH19), November 14-16, 2019. Denver, Colorado. pdf [300]
  • David (Ahmadreza) Mosallanezhad, Ghazaleh Beigi, and Huan Liu. ``Deep Reinforcement Learning-based Text Anonymization against Private-Attribute Inference", Conference on Emprirical Methods in National Language Processing (EMNLP2019), November 3-7, 2019. Hong Kong, China.  pdf
  • Suhang Wang, Charu Aggarwal, and Huan Liu. ``Beyond word2vec: Distance-graph Tensor Factorization for Word and Document Embeddings",   The 28th ACM International Conference on Information and Knowledge Management (CIKM2019), Novemember 3-7, 2019. Beijing, China. pdf
  •  Limeng Cui, Kai Shu, Suhang Wang, Dongwon Lee and Huan Liu. ``dEFEND: A System for Explainable Fake News Detection", Demo, The 28th ACM International Conference on Information and Knowledge Management (CIKM2019), Novemember 3-7, 2019. Beijing, China. pdf
  • Pradyumna Prakhar Sinha, Rohan Mishra, Ramit Sawhney, Debanjan Mahata, Rajiv Ratn Shah, and Huan Liu. ``#suicidal - A Multipronged Approach to Identify and Explore Suicidal Ideation in Twitter", The 28th ACM International Conference on Information and Knowledge Management (CIKM2019), Novemember 3-7, 2019. Beijing, China. pdf [295]
  • Ghazaleh Beigi, Kai Shu, Ruocheng Guo, Suhang Wang, and Huan Liu. ``Privacy Preserving Text Representation Learning", Poster, In the Proceedings of the 30th ACM Conference on Hypertext and Social Media (HT 2019), Sept 17-20, 2019. Hof, Germany.  pdf
  • Kai Shu, Xinyi Zhou, Suhang Wang, Reza Zafarani, and Huan Liu. ``The Role of User Profiles for Fake news Detection",  short paper, In Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), August 27 - 30, 2019. Vancouver, Canada. pdf
  • Jundong Li, Liang Wu, Ruocheng Guo, Chenghao Liu, Huan Liu. ``Multi-Level network Embedding with Boosted Low-Rank Matrix Approximation", In Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), August 27 - 30, 2019. Vancouver, Canada. pdf  
  • Thai Le, Kai Shu, Maria D. Molina, Dongwon Lee, S. Shyam Sundar, and Huan Liu.  ``Using Synthetic Clickbaits to Improve Prediction and Distinguish between Bot-Generated and Human-Written Headlines",  In Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), August 27 - 30, 2019. Vancouver, Canada.  news, pdf [290]
  • Adrienne Raglin, Anshuman Venkateswaran, and Huan Liu. ``Abductive Causal Reasoning for Internet of Things”, 5th IEEE International Conference on Internet of People (IoP2019) - Towards Collaborative Human and Machine Intelligence, August 19-23, 2019, Leicester, UK.
  • Lu Cheng, Jundong Li, Yasin N. Silva, Deborah Hall, and Huan Liu. ``PI-Bully: Personalized Cyberbullying Detection with Peer Influence", In Proceedings of the 2019 International Joint Conferences on Artifical Intelligence (IJCAI2019), August 10 -16, 2019. Macao, China. pdf
  • Kaize Ding, Jundong Li, Shivam Dhar, Shreyash Devan, and Huan Liu. ``InterSpot: InteractiveSpammer Detection in Social Media", Demo, In Proceedings of the 2019 International Joint Conferences on Artifical Intelligence (IJCAI2019), August 10 -16, 2019. Macao, China. pdf
  • Jundong Li, Ruocheng Guo, Chenghao Liu, Huan Liu. ``Adaptive Unsupervised Feature Selection on Attributed Networks  ",  In Proceedings of 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), August 4-8, 2019. Anchorage, Alaska. pdf
  • Kai Shu, Limeng Cui, Suhang Wang, Dongwon Lee, and Huan Liu. ``dEFEND: Explainable Fake News Detection",   In Proceedings of 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), August 4-8, 2019. Anchorage, Alaska.  pdf
  • Tahora H. Nazer, Matthew Davis, Mansooreh Karami, Leman Akoglu, David Koelle, and Huan Liu. ``Bot Detection: Will Focusing on Recall Cause Overall Performance Deterioration",  International Conference on Social Computing, Behavior-Culture Modeling, and Prediction (SBP-BRiMS 2019), July 9 - 12, 2019. Washington DC. pdf  data and code [285]
  •  Jayashree Subramanian*, Varun Sridharan*, Kai Shu, and Huan Liu. ``Exploiting Emojis for Sarcasm Detection".  International Conference on Social Computing, Behavior-Culture Modeling, and Prediction (SBP-BRiMS 2019), July 9 - 12, 2019. Washington DC. pdf
  • Kaize Ding, Jundong Li, Rohit Bhanushali, and Huan Liu. ``Deep Anomaly Detection on Attributed Networks with Graph Convolutional Networks". In Proceedings of the 2019 SIAM International Conferene on Data Mining (SDM19), Calgary, Cananda, May 2-4, 2019. pdf
  • Lu Cheng, Ruocheng Guo, Yasin N. Silva, Deborah Hall, and Huan Liu. ``Hierarchical Attention Networks for Cyberbullying Detection on the Instagram Social Network". In Proceedings of the 2019 SIAM International Conferene on Data Mining (SDM19), Calgary, Cananda, May 2-4, 2019. pdf
  • Shuo Yang, Kai Shu, Suhang Wang, Renjie Gu, Fan Wu, and Huan Liu. ``Unsupervised Fake News Detection on Social Media: A Generative Approach". In Proceedings of 33rd AAAI Conference on Artificial Intelligence (AAAI 2019). Honolulu, Hawaii. January 27 - Feruary 1, 2019. pdf
  • Lu Cheng, Jundong Li, Yasin Silva, Debora Hall, and Huan Liu. ``XBully: Cyberbullying Detection within a Multi-Modal Context". In the Proceedings of 12th ACM International Conference on Web Search and Data Mining (WSDM 2019). February 11-15, 2019. Melbourne, Australia. pdf [280]
  • Ghazaleh Beigi, Ruocheng Guo, Alex Nou, Yanchao Zhang, and Huan Liu. ``Protecting User Privacy: An Approach for Untraceable Web Browing History and Unambiguous User Profiles". In the Proceedings of 12th ACM International Conference on Web Search and Data Mining (WSDM 2019). February 11-15, 2019. Melbourne, Australia. pdf, the morning paper
  • Kaize Ding, Jundong Li, and Huan Liu. ``Interactive Anomaly Detection on Attributed Networks". In the Proceedings of 12th ACM International Conference on Web Search and Data Mining (WSDM 2019). February 11-15, 2019. Melbourne, Australia. pdf
  • Vineeth Rakesh, Suhang Wang, Kai Shu, and Huan Liu. ``Linked Variational AutoEncoders for Inferring Substituable and Supplementary Items". In the Proceedings of 12th ACM International Conference on Web Search and Data Mining (WSDM 2019). February 11-15, 2019. Melbourne, Australia. pdf
  • Kai Shu, Suhang Wang, and Huan Liu. ``Beyond News Content: The Role of Social Context for Fake News Detection". In the Proceedings of 12th ACM International Conference on Web Search and Data Mining (WSDM 2019). February 11-15, 2019. Melbourne, Australia. pdf, the morning paper

2018

  • Kai Shu, Suhang Wang, Thai Le, Dongwon Lee, and Huan Liu. ``Deep Headline Generation for Clickbait Detection". In the 2018 IEEE International Conference on Data Mining (ICDM2018). November 17 -20, 2018. Singapore. pdf [275]
  • Shan-Yun Teng, Jundong Li, Lo-Pang-Yun Ting, Kun-Ta Chuang, Huan Liu. ``Interactive Unknowns Recommendation in E-Learning Systems”. In the 2018 IEEE International Conference on Data Mining (ICDM2018). November 17 -20, 2018. Singapore. pdf
  • Junliang Yu, Min Gao, Jundong Li, Hongzhi Yin, and Huan Liu. ``Adaptive Implicit Friend Identification over Heterogeneous Networks for Social Recommendation". In Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM2018).  October 22 - 26, 2018. Turin, Italy.  pdf
  • Yiqi Chen, Tieyun Qian, Huan Liu, and Ke Sun. ```Bridge' Enhanced Signed Directed Network Embedding". In Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM2018).  October 22 - 26, 2018. Turin, Italy.  pdf, data and code
  • Liangyue Li, Hanghang Tong, and Huan Liu. ``Towards Explainable Networked Prediction". Short Paper. In Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM2018).  October 22 - 26, 2018. Turin, Italy.  pdf
  • Vineeth Rakesh, Ruocheng Guo, Raha Moraffah, Nitin Agarwal, and Huan Liu. ``Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects". Short Paper. In Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM2018).  October 22 - 26, 2018. Turin, Italy.  pdf [270]
  • Wen Zhang, Kai Shu, Suhang Wang, Huan Liu, and Yalin Wang. ``Multimodal Fusion of Brain Networks with Longitudinal Couplings", In 21th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2018). September 16 -20, 2018. Granada, Spain. pdf
  • Kai Shu, Suhang Wang, Jiliang Tang, Yi Chang, Ping Luo, and Huan Liu.  ``Exploiting User Actions for App Recommendations", Short Paper. In The 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2018). August 28 - 31, 2018. Barcelona, Spain. pdf
  • Nur Shazwani Kamarudin, Vineeth Rakesh Mohan, Ghazaleh Beigi, Lydia Manikonda and Huan Liu. ``A Study of Reddit-User’s Response to Rape", Poster Paper. In The 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2018). August 28 - 31, 2018. Barcelona, Spain. pdf
  • Guansong Pang, Longbing Cao, Ling Chen, and Huan Liu. ``Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection", In: 24th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD2018), August 19-23, 2018. London, UK.  pdf
  • Amy Sliva, Kai Shu, and Huan Liu.  ``Using Social Media to Understand Cyber Attack Behavior", In 9th International Conference on Applied Human Factors and Ergonomics (AHFE 2018), July 21 - 25, 2018. Orlando, Florida. pdf [265]
  • Ruocheng Guo, Jundong Li, and Huan Liu. ``INITIATOR: Noise-contrastive Estimation for Marked Temporal Point Process ", the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI-18), July 13-19, 2018. Stockholm, Sweden. pdf
  • Ghazaleh Beigi, Kai Shu, Yanchao Zhang, and Huan Liu. ``Securing Social Media User Data - An Adversarial Approach",  the 29th ACM Conference on HyperText and Social Media (HT-2018), July 9 - 12, 2018. Baltimore, Maryland.  pdf
  • Liang Wu, Diane Hu, Liangjie Hong, and Huan Liu. ``Turning Clicks into Purchases: Revenue Optimization for Product Search in E-Commerce", The 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2018), July 8 - 12, 2018. Ann Arbor, Michigan. pdf
  • Kathleen Carley, Guido Cervone, Nitin Agarwal, and Huan Liu. ``Social Cyber-Security", short paper, International Conference on Social Computing, Behavior-Culture Modeling, and Prediction (SBP-BRiMS 2018), July 10 - 13, 2018. Washington DC. [260]
  • Ghazaleh Beigi and Huan Liu. ``Similar but Different: Exploiting Users Congruity for Recommendation Systems", International Conference on Social Computing, Behavior-Culture Modeling, and Prediction (SBP-BRiMS 2018), July 10 - 13, 2018. Washington DC. pdf
  • Lydia Manikonda, Ghazaleh Beigi, Huan Liu and Subbarao Kambhampati. ``Twitter for Sparking a Movement, Reddit for Sharing the Moment: #metoo through the Lens of Social Media", short paper, International Conference on Social Computing, Behavior-Culture Modeling, and Prediction (SBP-BRiMS 2018), July 10 - 13, 2018. Washington DC. pdf
  • Kai Shu, Amy Sliva, Justin Sampson, and Huan Liu. ``Understanding Cyber Attack Behaviors with Sentiment Information on Social Media",  International Conference on Social Computing, Behavior-Culture Modeling, and Prediction (SBP-BRiMS 2018), July 10 - 13, 2018. Washington DC. pdf
  • Liang Wu, Jundong Li, Fred Morstatter, Huan Liu. ``Toward Relational Learning with Misinformation". The 18th SIAM International Conference on Data Mining (SDM 2018), May 3-5, 2018. San Diego, CA. pdf
  • Jundong Li, Chen Chen, Hanghang Tong, and Huan Liu. ``Multi-Layered Network Embedding".  The 18th SIAM International Conference on Data Mining (SDM 2018), May 3-5, 2018. San Diego, CA. pdf [255]
  • Jundong Li, Jiliang Tang, Yilin Wang, Yali Wan, Yi Chang and Huan Liu ``Understanding and Predicting Delay in Reciprocal Relations".  In Proceedings of the 27th International Conference on World Wide Web (WWW), Lyon, France, Apr 23-27, 2018. pdf
  • Kai Shu, Suhang Wang, Jiliang Tang, Yilin Wang, and Huan Liu.  ``CrossFire: Cross Media Joint Friend and Item Recommendations", The 11th ACM International Conference on Web Search and Data Mining  (WSDM2018), Los Angeles, CA. Feb 5-9, 2018. pdf
  • Liang Wu and Huan Liu. ``Tracing Fake-News Footprints: Characterizing Social Media Messages by How They Propagate",   The 11th ACM International Conference on Web Search and Data Mining  (WSDM2018), Los Angeles, CA. Feb 5-9, 2018. pdf
  • Jundong Li, Kewei Cheng, Liang Wu, and Huan Liu.  ``Streaming Link Prediction on Dynamic Attributed Networks ",  The 11th ACM International Conference on Web Search and Data Mining  (WSDM2018), Los Angeles, CA. Feb 5-9, 2018. pdf
  • Suhas Ranganath, Ghazaleh Beigi, and  Huan Liu. ``Leveraging Implicit Contribution Amounts to Facilitate Microfinancing Requests",  the 11th ACM International Conference on Web Search and Data Mining  (WSDM2018), Los Angeles, CA. Feb 5-9, 2018. pdf [250]
  • Xuying Meng, Suhang Wang, Huan Liu, and Yujun Zhang. ``Exploiting Emotion on Reviews for Recommender Systems", The Thirty-Second AAAI International Conference on AI (AAAI2018), New Orleans, Louisiana. Feb 2-7, 2018. pdf
  • Xuying Meng, Suhang Wang, Kai Shu, Jundong Li, Bo Chen, Huan Liu, and Yujun Zhang. ``Personalized Privacy-Preserving Social Recommendation" The Thirty-Second AAAI International Conference on AI (AAAI2018), New Orleans, Louisiana. Feb 2-7, 2018. pdf
  • Guansong Pang, Longbing Cao, Ling Chen, Defu Lian, and Huan Liu. ``Sparse Modeling-based Sequential Ensemble Learning for Effective Outlier Detection in High-dimensional Numeric Data" The Thirty-Second AAAI International Conference on AI (AAAI2018), New Orleans, Louisiana. Feb 2-7, 2018. pdf
  • Jundong Li, Liang Wu, Harsh Dani, and Huan Liu. ``Unsupervised Personalized Feature Selection" The Thirty-Second AAAI International Conference on AI (AAAI2018), New Orleans, Louisiana. Feb 2-7, 2018. pdf

2017

  • Jundong Li, Harsh Dani, Xia Hu, Jiliang Tang, Yi Chang, and Huan Liu. ``Attributed Network Embedding for Learning in a Dynamic Environment", In Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM2017), Singapore, Nov 6-10, 2017. pdf [245]
  • Suhang Wang, Charu Aggarwal, Jiliang Tang, and Huan Liu. ``Attributed Signed Network Embedding", In Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM2017), Singapore, Nov 6-10, 2017. pdf
  • Harsh Dani, Jundong Li, and Huan Liu. ``Sentiment Informed Cyberbullying Detection in Social Media", The European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017), Skopje, Macedonia. September 18 - 22, 2017. pdf
  • Jundong Li, Harsh Dani, Xia Hu, and Huan Liu. ``Radar: Residual Analysis for Anomaly Detection in Attributed Networks", In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, Aug 19-25, 2017. pdf
  • Jundong Li, Jiliang Tang, and Huan Liu. ``Reconstruction-based Unsupervised Feature Selection: An Embedded Approach", In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, Aug 19-25, 2017. pdf
  • Guansong Pang, Longbing Cao, Ling Chen, and Huan Liu. ``Learning Homophily Couplings from Non-IID Data for Joint Feature Selection and Noise-Resilient Outlier Detection",  In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, Aug 19-25, 2017. pdf [240]
  • Kewei Cheng, Jundong Li, and Huan Liu. ``Unsupervised Feature Selection in Signed Social Networks", In Proceedings of 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Halifax, Canada, Aug 13-17, 2017. pdf
  • Suhang Wang, Charu Aggarwal, Huan Liu. ``Randomized Feature Engineering as a Fast and Accurate Alternative to Kernel Methods", In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Halifax, Canada, Aug 13-17, 2017. pdf
  • Liang Wu, Xia Hu, Fred Morstatter, Huan Liu. ``Adaptive Spammer Detection with Sparse Group Modeling'', the 11th AAAI International Conference on Web and Social Media (ICWSM 2017), May 15-18, 2017. Montreal, Canada. pdf
  • Liang Wu, Xia Hu, Huan Liu. ``Early Identification of Personalized Trending Topics in Microblogging'', poster paper, the 11th AAAI  International Conference on Web and Social Media (ICWSM 2017), May 15-18, 2017. Montreal, Canada. pdf
  • Liang Wu, Xia Hu, Fred Morstatter, Huan Liu. ``Detecting Camouflaged Content Polluters'', poster paper, the 11th AAAI International Conference on Web and Social Media (ICWSM 2017), May 15-18, 2017. Montreal, Canada. pdf  [235]
  • Robert Trevino, Thomas J. Lamkin, Ross Smith, Steve A. Kawamoto, Huan Liu. ``Maximum Distance Minimum Error (MDME): A Non-parametric Approach to Feature Selection for Image-Based High Content Screening Data", IEEE Intelligent Systems Conference (IntelliSys2017). September 7-8, 2017. London, United Kingdom.
  • Liang Wu, Jundong Li, Xia Hu, Huan Liu. ``Gleaning Wisdom from the Past: Early Detection of Emerging Rumors in Social Media", SIAM International Conference on Data Mining (SDM17), April 27-29, 2017. Houston, Texas. pdf
  • Suhang Wang, Charu Aggarwal, and Huan Liu. ``Using a Random Forest to Inspire a Neural Network and Improving on It", SIAM International Conference on Data Mining (SDM17), April 27-29, 2017. Houston, Texas. pdf
  • Suhang Wang, Yilin Wang, Jiliang Tang, Charu Aggarwal, Suhas Ranganath, and Huan Liu. ``Exploiting Hierarchical Structures for Unsupervised Feature Selection", SIAM International Conference on Data Mining (SDM17), April 27-29, 2017. Houston, Texas. pdf
  • Suhang Wang, Jiliang Tang, Charu Aggarwal, Yi Chang, and Huan Liu. ``Signed Network Embedding in Social Media", SIAM International Conference on Data Mining (SDM17), April 27-29, 2017. Houston, Texas. pdf [230]
  • Jundong Li, Liang Wu, Osmar R. Zaïane and Huan Liu. ``Toward Personalized Relational Learning",  SIAM International Conference on Data Mining (SDM17), April 27-29, 2017. Houston, Texas. pdf
  • Suhang Wang, Yilin Wang, Jiliang Tang, Kai Shu, Suhas Ranganath, and Huan Liu. ``Exploiting Visual Contents for Point-of-Interest Recommendation",  The 26th International World Wide Web Conference (WWW17), April 3-7, 2017. Perth, Australia. pdf
  • Robert P. Trevino, Philippe Faucon, Thomas J. Lamkin, Steve A. Kawamoto, Ross Smith and Huan Liu. ``Non-parametric Quality Assessment of High-Content Screening Assays", the 9h International Conference on Bioinformatics and Computational Biology (BICOB2017), March 20-22, 2017. Honolulu, HI. (nominated for Best Paper Award)
  • Yilin Wang, Suhang Wang, Jiliang Tang, Guojun Qi, Huan Liu, and Baoxin Li. ``CLARE: A Joint Approach to Label Classification and Tag Recommendation", The Thirty First AAAI Conference (AAAI2017) February 4-9, 2017. San Francisco, CA. pdf
  • Kewei Cheng, Jundong Li, Jiliang Tang, and Huan Liu. ``Unsupervised Sentiment Analysis with Signed Social Networks", The Thirty First AAAI Conference (AAAI2017) February 4-9, 2017. San Francisco, CA. pdf [225]

2016

  • Jundong Li, Xia Hu, Ling Jian, and Huan Liu. ``Toward Time-Evolving Feature Selection on Dynamic Networks", In Proceedings of IEEE International Conference on Data Mining (ICDM2016), short paper, December 13-15, 2016. Barcelona, Spain. pdf
  • Guansong Pang, Longbing Cao, Ling Chen, and Huan Liu. ``Unsupervised Feature Selection for Outlier Detection by Modelling Hierarchical Value-Feature Couplings", In Proceedings of IEEE International Conference on Data Mining (ICDM2016), December 13-15, 2016. Barcelona, Spain. pdf
  • Justin Sampson, Fred Morstatter, Liang Wu and Huan Liu. ``Leveraging the Implicit Structure within Social Media for Emergent Rumor Detection", short paper, ACM International Conference of Information and Knowledge Management (CIKM2016), October 24-28, 2016. Indianapolis, Indiana. pdf
  • Suhang Wang, Jiliang Tang, Fred Morstatter and Huan Liu. ``Paired Restricted Boltzmann Machine for Linked Data", ACM International Conference of Information and Knowledge Management (CIKM2016), October 24-28, 2016. Indianapolis, Indiana. pdf
  • Suhang Wang, Jiliang Tang, Charu Aggarwal and Huan Liu. ``Linked Document Embedding for Classification", ACM International Conference of Information and Knowledge Management (CIKM2016), October 24-28, 2016. Indianapolis, Indiana. pdf [220]
  • Kewei Cheng, Jundong Li and Huan Liu. ``FeatureMiner: A Tool for Interactive Feature Selection", demo paper, ACM International Conference of Information and Knowledge Management (CIKM2016), October 24-28, 2016. Indianapolis, Indiana. pdf
  • Fred Morstatter, Liang Wu, Tahora H. Nazer, Kathleen M. Carley, and Huan Liu. ``A New Approach to Bot Detection: Striking the Balance Between Precision and Recall", IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM2016), August 18-21, San Francisco, CA. pdf
  • Fred Morstatter and Huan Liu. ``A Novel Measure for Coherence in Statistical Topic Models", short paper, Association of Computational Linguistics (ACL), August 7 - 12, 2016. Berlin, Germany. pdf
  • Ling JianJundong Li, Kai Shu, and Huan Liu. ``Multi-Label Informed Feature Selection", In Proceedings of 25th International Joint Conference on Artificial Intelligence (IJCAI), July 9-15, 2016. New York. pdf
  • Yilin Wang, Suhang Wang, Jiliang Tang, Huan Liu and Baoxin Li. ``PPP: Joint Pointwise and Pairwise Image Label Prediction",  CVPR2016, June 27-30, 2016. Las Vegas, Nevada.  pdf [215]
  • Ghazaleh Beigi, Jiliang Tang and Huan Liu. ``Signed Link Analysis in Social Media Networks",  poster paper, The 10th International AAAI Conference on Weblogs and Social Media (ICWSM2016), May 17 - 20, 2016. Cologne, Germany. pdf
  • Suhas Ranganth, Xia Hu, Jiliang Tang, Suhang Wang and Huan Liu. ``Understanding and Identifying Rhetorical Questions in Social Media", poster paper, The 10th International AAAI Conference on Weblogs and Social Media (ICWSM2016), May 17 - 20, 2016. Cologne, Germany. pdf
  • Isaac Jones, Ran Wang, Jiawei Han and Huan Liu.``Community Cores: Removing Size Bias From Community Detection", poster paper, The 10th International AAAI Conference on Weblogs and Social Media (ICWSM2016), May 17 - 20, 2016. Cologne, Germany. pdf
  • Pritam Gundecha, Jiliang Tang, Xia Hu and Huan Liu. ``Exploring Personal Attributes from Unprotected Interactions", poster paper, The 10th International AAAI Conference on Weblogs and Social Media (ICWSM2016), May 17 - 20, 2016. Cologne, Germany. pdf
  • Jinxue Zhang, Xia Hu, Yanchao Zhang and Huan Liu. ``Your Age Is No Secret: Inferring Microbloggers' Ages via Content and Interaction Analysis", The 10th International AAAI Conference on Weblogs and Social Media (ICWSM2016), May 17 - 20, 2016. Cologne, Germany. pdf [210]
  • Ghazaleh Beigi, Jiliang Tang, Suhang Wang, and Huan Liu. ``Exploiting Emotional Information for Trust/Distrust Prediction". SIAM International Conference on Data Mining (SDM16),  May 5-7, 2016. Miami, Florida. pdf
  • Jiliang Tang, Charu Aggarwal, and Huan Liu. ``Node Classification in Signed Social Networks ". SIAM International Conference on Data Mining (SDM16),  May 5-7, 2016. Miami, Florida. pdf
  • Jundong Li, Xia Hu, Liang Wu, and Huan Liu. ``Robust Unsupervised Feature Selection on Networked Data". SIAM International Conference on Data Mining (SDM16),  May 5-7, 2016. Miami, Florida. pdf
  • Fred Morstatter, Harsh Dani, Justin Sampson and Huan Liu. ``Can One Tamper with the Sample API? -Toward Neutralizing Bias from Spam and Bot Content". Best WWW2016 Poster. The 25th International World Wide Web Conference (WWW16), April 11 - 15, 2016. Montreal, Canada. pdf
  • Jiliang Tang, Charu Aggarwal, and Huan Liu. ``Recommendation with Signed Social Networks". The 25th International World Wide Web Conference (WWW16), April 11 - 15, 2016. Montreal, Canada. pdf [205]
  • Liang Wu, Xia Hu, and Huan Liu. ``Relational Learning with Social Status Analysis". ACM International Conference on Web Search and Data Mining (WSDM2016), February 22-25, 2016. San Francisco, CA. pdf
  • Suhas Ranganath, Xia Hu, Jiliang Tang, and Huan Liu. ``Understanding and Identifying Advocates of Political Campaigns on Social Media". ACM International Conference on Web Search and Data Mining (WSDM2016), February 22-25, 2016. San Francisco, CA. pdf
  • Jiliang Tang, SuhangWang, Xia Hu, Dawei Yin, Yingzhou Bi, Yi Chang,  and Huan Liu. ``Recommendation with Social Dimensions", The Thirtieth AAAI Conference (AAAI2016), February 12-17, 2016. Phoenix, Arizona. pdf
  • Suhas Ranganath, Fred Morstatter, Xia Hu, Jiliang Tang, Suhang Wang, and Huan Liu. ``Predicting Online Protest Participation of Social Media Users", The Thirtieth AAAI Conference (AAAI2016), February 12-17, 2016. Phoenix, Arizona. pdf

2015

  • Suhas Ranganth, Suhang Wang, Xia Hu, Jiliang Tang, and Huan Liu.``Finding Time-Critical Replies for Information Seeking in Social Media". In Proceedings of IEEE International Conference on Data Mining (ICDM2015), November 14 - 17, 2015. Atlantic City, NJ. pdf [200]
  • Justin Sampson,  Fred Morstatter, Reza Zafarani, and Huan Liu. ``Real-time Crisis Mapping using Language Distributions". Demo. In Proceedings of IEEE International Conference on Data Mining (ICDM2015), November 14 - 17, 2015. Atlantic City, NJ. pdf
  • Harsh Dani, Fred Morstatter, Xia Hu, Zhen Yang, and Huan Liu. ``Social Answer:  A System for Finding Appropriate Sites for Questions in Social Media". Demo. In Proceedings of IEEE International Conference on Data Mining (ICDM2015), November 14 - 17, 2015. Atlantic City, NJ. pdf
  • Robert P. Trevino, Steve A. Kawamoto, Thomas J. Lamkin, and Huan Liu. ``Cell Analytics in Compound Hit Selection of Bacterial Inhibitors". In Proceedings of IEEE International Conference on Big Data (IEEE BigData 2015), October 29 - November 1, 2015. Santa Clara, CA.  pdf
  • Yunzhong Liu, Yi Chen, Jiliang Tang, and Huan Liu. ``Context-Aware Expeience Extraction from Online Health Forums". IEEE International Conference on Healthcare Informatics (ICHI2015), October 21-23, 2015. Dallas Texas. pdf
  • Reza Zafarani and Huan Liu. ``10 Bits of Surprise: Detecting Malicious Users with Minimum Information". ACM International Conference of Information and Knowledge Management (CIKM2015), October 19-23, 2015. Melbourne, Australia. pdf [195]
  • Jundong Li, Jiliang Tang, Xia Hu, and Huan Liu. ``Unsupervised Streaming Feature Selection in Social Media". ACM International Conference of Information and Knowledge Management (CIKM2015), October 19-23, 2015. Melbourne, Australia. pdf
  • Suhang Wang, Jiliang Tang, and Huan Liu. ``Toward Dual Roles of Users in Recommender Systems". ACM International Conference of Information and Knowledge Management (CIKM2015), October 19-23, 2015. Melbourne, Australia. pdf
  • Fred Morstatter, Jürgen Pfeffer, Katja Mayer and Huan Liu. ``Text, Topics, and Turkers: Evaluation of Statistical Topics", the 26th ACM Conference on Hypertext and Social Media (Hypertext2015), September 1-4, 2015. Cyprus. pdf
  • Justin Sampson, Fred Morstatter, Ross Maciejewski and Huan Liu. ``Surpassing the Limit: Keyword Clustering to Improve Twitter Sample Coverage", the 26th ACM Conference on Hypertext and Social Media (Hypertext2015), September 1-4, 2015. Cyprus. pdf
  • Shamanth Kumar, Huan Liu, Sameep Mehta, and L. Venkata Subramaniam. ``Exploring a Scalable Solution to Identifying Events in Noisy Twitter Streams", short paper, IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM2015), August 25-28, 2015, Paris, France. pdf [190]
  • Zhen Yang, Isaac Jones, Xia Hu, and Huan Liu. ``Finding the Right Social Media Site for Questions", short paper, IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM2015), August 25-28, 2015, Paris, France. pdf
  • Wei Wei, Kenneth Joseph, Huan Liu, and Kathleen Carley. ``The Fragility of Twitter Social Networks Against Suspended Users". IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM2015), August 25-28, 2015, Paris, France. pdf
  • Suhang Wang, Jiliang Tang, Yilin Wang, and Huan Liu. ``Exploring Implicit Hierarchical Structures for Recommender Systems", the Proceedings of IJCAI 2015, July 25 - 31, 2015. Buenos Aires, Argentina. pdf
  • Yilin Wang, Suhang Wang, Jiliang Tang, Huan Liu, and Baoxin Li. ``Unsupervised Sentiment Analysis for Social Media Images", the Proceedings of IJCAI 2015, July 25 - 31, 2015. Buenos Aires, Argentina. pdf
  • Jiliang Tang, Chikashi Nobata, Anlei Dong, Yi Chang, and Huan Liu. ``Propagation-based Sentiment Analysis for Microblogging Data", SIAM International Conference on Data Mining (SDM15),  April 30 - May 2, 2015. Vancouver, British Columbia, Canada. pdf  [185]
  • Yu Cheng, Ankit Agrawal, Alok Choudhary, and Huan Liu. ``Legislative Prediction with Dual Uncertainty Minimization from Heterogeneous Information ", SIAM International Conference on Data Mining (SDM15),  April 30 - May 2, 2015. Vancouver, British Columbia, Canada.
  • Jiliang Tang, Shiyu Chang, Charu Aggarwal, and Huan Liu. ``Negative Link Prediction in Social Media". ACM International Conference on Web Search and Data Mining (WSDM2015), February 2-6, 2015. Shanghai, China. pdf
  • Ashwin Rajadesingan, Reza Zafarani and Huan Liu. ``Sarcasm Detection on Twitter: A Behavioral Modeling Approach". ACM International Conference on Web Search and Data Mining (WSDM2015), February 2-6, 2015. Shanghai, China. pdf
  • Suhas Ranganath, Jiliang Tang, Xia Hu, Hari Sundaram and Huan Liu. ``Leveraging Social Foci for Information Seeking in Social Media". The 29th AAAI Conference on Aritifical Intelligence (AAAI2015), Januray 25- 30, 2015. Austin, TX. pdf
  • Huiji Gao, Jiliang Tang, Xia Hu and Huan Liu. ``Content-Aware Point of Interest Recommendation on Location-Based Social Networks". The 29th AAAI Conference on Aritifical Intelligence (AAAI2015), Januray 25- 30, 2015. Austin, TX. pdf [180]
  • Suhang Wang, Jiliang Tang, and Huan Liu. ``Embedded Unsupervised Feature Selection". The 29th AAAI Conference on Aritifical Intelligence (AAAI2015), Januray 25- 30, 2015. Austin, TX. pdf

2014

  • Xia Hu, Jiliang Tang, Huiji Gao, and Huan Liu. "Social Spammer Detection with Sentiment Information". In Proceedings of the IEEE International Conference on Data Mining (ICDM 2014). December 14-17, 2014. Shenzhen, China. pdf
  • Yu Cheng, Alok Choudhary, Ankit Agrawal, Huan Liu, and Tao Zhang. ``Social Role Identification via Dual Role Uncertainty Minimization", In Proceedings of the IEEE International Conference on Data Mining (ICDM 2014). December 14-17, 2014. Shenzhen, China.
  • Xinxin Zhao, HuijiGao, Lingjun Li, Huan Liu, and Guoliang Xue. “An Efficient Privacy Preserving Location Based Service System”, IEEE GLOBECOM2014 - Communication and Information System Security Symposium, December 8-12, 2014. Austin, TX.
  • Jiliang Tang, Xia Hu, Yi Chang, and Huan Liu. ``Predictability of Distrust with Interaction Data", ACM International Conference of Information and Knowledge Management (CIKM2014), November 3-7, 2014. Shanghai, China. pdf [175]
  • Fred Morstatter, Shamanth Kumar, Joshua Stiefer, Justin Sampson, Daniel Howe, Grant Marshall, David Kahn, Terrance Williams, Wesley Bowman, and Huan Liu. ``CrisisTracker: Connecting First Responders to Twitter Analysis", IEEE Global Humanitarian Technology Conference (GHTC), poster, October 10 - 13, 2014. Silicon Valley/San Jose, CA.
  • Jiliang Tang, Xia Hu, and Huan Liu. ``Is Distrust the Negation of Trust? The Value of Distrust in Social Media", 25th ACM Conference on Hypertext and Social Media (Hypertext2014), 1–4 Sep 2014, Santiago, Chile. pdf
  • Shamanth Kumar, Xia Hu, and Huan Liu. ``A Behavior Analytics Approach to Identifying Tweets from Crisis Regions", short paper, 25th ACM Conference on Hypertext and Social Media (Hypertext2014), 1–4 Sep 2014, Santiago, Chile. pdf
  • Mohammad Ali Abbasi, Jiliang Tang, and Huan Liu. ``Scalable Learning of Users' Preferences Using Networked Data", 25th ACM Conference on Hypertext and Social Media (Hypertext2014), 1–4 Sep 2014, Santiago, Chile. pdf [170]
  • Mohammad Ali Abbasi, Reza Zafarani and Huan Liu. `` Am I More Similar to My Followers or Followees? Homophily Effect in Directed Online Social Networks", short paper, 25th ACM Conference on Hypertext and Social Media (HT2014), 1–4 Sep 2014, Santiago, Chile. pdf
  • Xia Hu, Jiliang Tang, and Huan Liu. "Online Social Spammer Detection". The 28th AAAI Conference on Artificial Intelligence (2014). July 27-31, 2014. Quebec City, Quebec, Canada. pdf
  • Xia Hu, Jiliang Tang, and Huan Liu. ``Leveraging Knowledge across Media for Spammer Detection in Microblogging". In Proceedings of the 37th Annual ACM SIGIR Conference (SIGIR 2014). July 6-11, 2014. Gold Coast, Australia. pdf
  • Reza Zafarani and Huan Liu. ``Users Joining Multiple Sites: Distributions and Patterns", poster. The Eighth International AAAI Conference on Weblogs and Social Media (ICWSM 2014) , June 2-4, 20114. Ann Arbor, MI. pdf
  • Fred Morstatter, Jurgen Pfeffer, and Huan Liu. ``When is it Biased? Assessing the Representativeness of Twitter's Streaming API", poster paper, The 23rd International World Wide Web Conference, WWW2014 Web Science Track. April 10-11, 2014. Seoul, Korea. pdf [165]
  • Jiliang Tang and Huan Liu. ``Discriminant Analysis for Unsupervised Feature Selection", SIAM International Conference on Data Mining (SDM14),  April 24 -26, 2014. poster presentation. Philadelphia, Pennsylvania. pdf
  • Reza Zafarani and Huan Liu. ``Finding Friends on a New Site Using Minimum Information", SIAM International Conference on Data Mining (SDM14),  April 24 -26, 2014. poster presentation. Philadelphia, Pennsylvania. pdf
  • Ashwin Rajadesingan and Huan Liu. ``Identifying Users with Opposing Opinions in Twitter Debates", International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP14), April 2-5, 2014. Washington, D.C. pdf

2013

  • Huiji Gao, Jiliang Tang, Xia Hu, and Huan Liu. ``Modeling Temporal Effects of Human Mobile Behavior on Location-Based Social Networks", ACM International Conference of Information and Knowledge Management (CIKM2013), short paper, October 27 - November 1, 2013. San Francisco, CA. pdf
  • Pritam Gundecha, Feng Zhuo, and Huan Liu. ``Seeking Provenance of Information in Social Media", ACM International Conference of Information and Knowledge Management (CIKM2013), short paper, October 27 - November 1, 2013. San Francisco, CA. pdf [160]
  • Suhas Ranganath, Pritam Gundecha, and Huan Liu. ``A Tool for Assisting Provenance Search in Social Media", Demo, ACM International Conference of Information and Knowledge Management (CIKM2013), October 27 - November 1, 2013. San Francisco, CA. pdf
  • Huiji Gao, Jiliang Tang, Xia Hu, and Huan Liu. ``Exploring Temporal Effects for Location Recommendation on Location-Based Social Networks", the ACM Conference Series on Recommender Systems (RecSys2013), October 12-16, 2013. Hong Kong, China. pdf
  • Jiliang Tang, Huiji Gao, Xia Hu, and Huan Liu. ``Context-Aware Review Helpfulness Rating Prediction", the ACM Conference Series on Recommender Systems (RecSys2013), October 12-16, 2013. Hong Kong, China. pdf
  • Huiji Gao, Xufei Wang, Jiliang Tang, and Huan Liu. ``Network Denoising in Social Media", the 2013 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM2013), August 25-28, 2013. Niagara Falls, Canada. pdf
  • Zhuo Feng, Pritam Gundecha, and Huan Liu. "Recovering Information Recipients in Social Media via Provenance" the 2013 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM2013), short paper, August 25-28, 2013. Niagara Falls, Canada. pdf  [155]
  • Reza Zafarani and Huan Liu. ``Connecting Users across Social Media Sites: A Behavioral-Modeling Approach", oral presentation, the Nineteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'2013), August 11 - 14, 2013. Chicago, Illinois. pdf video lecture
  • Fred Morstatter, Shamanth Kumar, Huan Liu and Ross Maciejewski. ``Understanding Twitter Data with TweetXplorer", Demo, the Nineteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'2013), August 11 - 14, 2013. Chicago, Illinois. pdf
  • Pritam Gundecha, Suhas Ranganath, Zhuo Feng and Huan Liu. ``A Tool for Collecting Provenance Data in Social Media", Demo, the Nineteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'2013), August 11 - 14, 2013. Chicago, Illinois. pdf
  • Xia Hu, Jiliang Tang, Yanchao Zhang, and Huan Liu. "Social Spammer Detection in Microblogging", the Proceedings of IJCAI 2013, August 3-9, 2013. Beijing, China. pdf
  • Jiliang Tang, Huiji Gao, Xia Hu, and Huan Liu. "Exploiting Local and Global Social Context for Recommendation", the Proceedings of IJCAI 2013, August 3-9, 2013. Beijing, China. pdf [150]
  • Fred Morstatter, Jürgen Pfeffer, Huan Liu and Kathleen Carley. "Is the Sample Good Enough? Comparing Data from Twitter's Streaming API with Twitter's Firehose",  the Seventh International AAAI Conference on Weblogs and Social Media (ICWSM 2013) , July 8-10, 20113. Boston, MA. pdf, blog post
  • Xia Hu, Jiliang Tang, Huiji Gao and Huan Liu. "Unsupervised Sentiment Analysis with Emotional Signals", the 22nd International World Wide Web Conference (WWW2013). May 13 - 17, 2013. Rio de Janeiro, Brazil. pdf
  • Jiliang Tang, Xia Hu, Huiji Gao, and Huan Liu. "Unsupervised Feature Selection for Multi-View Data in Social Media", the 13th SIAM International Conference on Data Mining (SDM 2013). May 2-4, 2013. Austin, Texas. pdf
  • Jiliang Tang and Huan Liu. ``CoSelect: Feature Selection with Instance Selection for Social Media Data'', the 13th SIAM International Conference on Data Mining (SDM 2013). May 2-4, 2013. Austin, Texas. pdf
  • Xia Hu, Jiliang Tang, Huiji Gao, and Huan Liu. "ActNeT: Active Learning for Networked Texts in Microblogging", the 13th SIAM International Conference on Data Mining (SDM 2013). May 2-4, 2013. Austin, Texas. pdf [145]
  • Shamanth Kumar, Fred Morstatter, Reza Zafarani, and Huan Liu. "Whom Should I Follow? Identifying Relevant Users in a Crisis", the 24th ACM Conference on Hypertext and Social Media (HT2013), 1–3 May 2013, Paris, France. pdf  New Scientist
  • Mohammad Ali Abbasi and Huan Liu. "Measuring User Credibility in Social Media", poster paper, International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP13), April 2-5, 2013. Washington, D.C. pdf
  • Xia Hu, Lei Tang, Jiliang Tang, and Huan Liu. "Exploiting Social Relations for Sentiment Analysis in Microblogging", the Sixth ACM International Conference on Web Search and Data Mining (WSDM2013). Best Paper Shortlist. February 4-8, 2013. Rome, Italy. pdf
  • Jiliang Tang, Huiji Gao, Xia Hu, and Huan Liu. "Exploiting Homophily Effect for Trust Prediction", the Sixth ACM International Conference on Web Search and Data Mining (WSDM2013). February 4-8, 2013. Rome, Italy. pdf.

2012

  • Salem Alelyani and Huan Liu."Supervised Low Rank Matrix Approximation for Stable Feature Selection". In the 11th International Conference on Machine Learning and Applications. December,  2012. Boca Raton, Florida. pdf  [140]
  • Huiji Gao, Jiliang Tang, and Huan Liu. " gSCorr: Modeling Geo-Social Correlations for New Check-ins on Location-Based Social Networks", the 21st ACM Conference on Information and Knowledge Management (CIKM2012), short paper, October 29 - November 2, 2012. Maui, Hawaii. pdf.
  • Shamanth Kumar, Fred Morstatter, Grant Marshall, Huan Liu, and Ullas Nambiar. "Navigating Information Facets on Twitter (NIF-T)", Demo, the Eighteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2012), Beijing, August 12-16, 2012. pdf, video clip
  • Jiliang Tang, Huiji Gao, Huan Liu, and Artish Das Sarma. "eTrust: Understanding Trust Evolution in an Online World," the Eighteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2012, Beijing, August 12-16, 2012). pdf , video clip
  • Jiliang Tang and Huan Liu. "Unsupervised Feature Selection for Linked Social Media Data", the Eighteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2012), Beijing, August 12-16, 2012. pdf,  video clip
  • Guanfeng Liu, Yan Wang, Mehmet A. Orgun and Huan Liu, Discovering Trust Networks for the Selection of Trustworthy Service Providers in Complex Contextual Social Networks, IEEE 9th International Conference on Web Services (IEEE ICWS 2012), June 24-29, Honolulu, Hawaii, USA. pdf [135]
  • Huiji Gao, Jiliang Tang, and Huan Liu. ``Exploring Social-Historical Ties on Location-Based Social Networks", the Sixth International AAAI Conference on Weblogs and Social Media (ICWSM2012), Dublin, Ireland. June 4-6, 2012. pdf.
  • Xia Hu and Huan Liu. ``Social Status and Role Analysis of Palin's Email Network", International Conference on World Wide Web WWW2012, poster, Lyon, France. April 16-20, 2012. pdf
  • Jiliang Tang and Huan Liu. "Feature Selection with Linked Data in Social Media", the 12th SIAM International Conference on Data Mining (SDM2012), April 26-28, 2012. Anaheim, California. pdf
  • Mohammad-Ali Abbasi, Sun-Ki Chai, Huan Liu, and Kiran Sagoo. "Real-World Behavior Analysis through a Social Media Lens", International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP12), April 3-5, 2012. College Park, MD. Best Student Paper Award (Runner Up). pdf [130]
  • Mohammad-Ali Abbasi, Shamanth Kumar, Jose Augusto Andrade Filhoe, and Huan Liu. "Lessons Learned in Using Social Media for Disaster Relief - ASU Crisis Response Game", International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP12), poster, April 3-5, 2012. College Park, MD. pdf
  • Jiliang Tang, Huiji Gao, and Huan Liu. "mTrust: Discerning Multi-Faceted Trust in a Connected World", the 5th ACM International Conference on Web Search and Data Mining (WSDM 2012), February 8-12, 2012. Seattle, Washington. pdf

2011

  • Xufei Wang, Jiliang Tang, and Huan Liu. "Document Clustering via Matrix Representation", the 11th IEEE International Conference on Data Mining  (ICDM2011), December 11 - 14, 2011. Vancouver, Canada. pdf
  • Salem Alelyani, Lei Wang, and Huan Liu. "The Effect of the Characteristics of the Dataset on the Selection Stability", the 23rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI2011), November 7 - 9, 2011. Boca Raton, Florida. pdf
  • Jose Augusto Andrade Filho, Andre Carlos Ponce De Leon Ferreira Carvalho, Rodrigo Fernandes Mello, Salem Alelyani and Huan Liu. "Quantifying Features Using False Nearest Neighbors: An Unsupervised Approach", the 23rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI2011), November 7 - 9, 2011. Boca Raton, Florida. pdf [125]
  • Xia Hu, Lei Tang, and Huan Liu. "Enhancing Accessibility of Microblogging Messages Using Semantic Knowledge", the 20th ACM Conference on Information and Knowledge Management (CIKM2011), poster paper, October 24-28, 2011. Glasgow, UK. pdf
  • Xufei Wang, Huan Liu, and Wei Fan. "Connecting Users with Similar Interests via Tag Network Inference", the 20th ACM Conference on Information and Knowledge Management (CIKM2011), short paper, October 24-28, 2011. Glasgow, UK. pdf
  • Pritam Gundecha, Geoffrey Barbier, and Huan Liu. "Exploiting Vulnerability to Secure User Privacy on a Social Networking Site", the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2011), August 21-24, 2011, San Diego, CA. pdf
  • Shamanth Kumar, Reza Zafarani, and Huan Liu. "Understanding User Migration Patterns in Social Media ", the special track on AI and the Web (AIW) at the Twenty-Fifth AAAI Conference on Artificial Intelligence (2011). August 7 - 11, 2011, in San Francisco, CA. pdf
  • Shamanth Kumar, Geoffrey Barbier, Mohammad Ali Abbasi, and Huan Liu. "TweetTracker: An Analysis Tool for Humanitarian and Disaster Relief, " Demo, 5th International AAAI Conference on Weblogs and Social Media (ICWSM-11), July 17-21, 2011. Barcelona, Spain.
  • Anirudh Kondaveeti, George Runger, Huan Liu and Jeremy Rowe. "Extracting Geographic Knowledge from Sensor Intervention Data Using Spatial Association Rules", the First IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM 2011), June 28 - July 1, Fuzhou, China. [120]
  • Gabriel Pui Cheong Fung, Fred Morstatter, and Huan Liu. ``Feature Selection Strategy in Text Classification", The 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2011), May 24-27, 2011, Shenzhen, China.
  • Huiji Gao, Xufei Wang, Geoffrey Barbier, and Huan Liu. Promoting Coordination for Disaster Relief - From Crowdsourcing to Coordination. SBP 2011: 197-204
  • Geoffrey Barbier, and Huan Liu. Information Provenance in Social Media. SBP 2011: 276-283

2010 and earlier

  • Xufei Wang, Lei Tang, Huiji Gao, and Huan Liu. Discovering Overlapping Groups in Social Media. In Proceedings of the 10th IEEE International Conference on Data Mining (ICDM'10), 2010.
  • M. Dash and H. Liu, "Feature Selection for Clustering", pp 110 -- 121, PAKDD 2000, Kyoto, Japan. April, 2000. Springer. ( ``the Most Influential Paper" award at PAKDD 2010, 10 years after its publication at PAKDD 2000) postscript.
  • Zheng Zhao, Lei Wang, and Huan Liu. ``Efficient Spectral Feature Selection with Minimum Redundancy". In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, Atlanta, Georgia, USA, July 11–15, 2010. pdf
  • Zheng Zhao, Jiangxin Wang, Shashvata Sharma, Nitin Agarwal, Huan Liu, and Yung Chang. ``An Integrative Approach to Identifying Biologically Relevant Genes", SIAM International Conference on Data Mining (SDM'10), Columbus, Ohio. April 29 - May 1, 2010. [115] pdf
  • Lei Tang, Geoffrey Barbier, Huan Liu and Jianping Zhang. ``A Social Network Analysis Approach to Detecting Suspicious Online Financial Activities". In Proceedings of International Conference on Social Computing, Behavioral Modeling and Prediction (SBP’10), pages 390-397, March 29 - April 1, 2010.pdf
  • Shamanth Kumar, Reza Zafarani, Mohammad Ali Abbasi, Geoffrey Barbier, Huan Liu. ``Convergence of Influential Bloggers for Topic Discovery in the Blogosphere". In Proceedings of International Conference on Social Computing, Behavioral Modeling and Prediction (SBP'10), pages 406-412, March 29 - April 1, 2010. pdf
  • Reza Zafarani, William D. Cole, Huan Liu. Sentiment Propagation in Social Networks: A Case Study in Live
  • . In Proceedings of International Conference on Social Computing, Behavioral Modeling and Prediction (SBP'10), pages 413-420, March 29 - April 1, 2010. pdf
  • Zheng Zhao, Jiangxin Wang, Huan Liu, Yun Chang. ``Biological relevance Detection via Network Dynamic Analysis", 2nd International Conference on Bioinformatics and Computational Biology (BICoB), Honolulu, Hawaii. March 24 - 26, 2010.  pdf  Best Paper Award
  • Nitin Agarwal, Huan Liu, Shankara Subramanya, John Salerno, and Philip Yu. "Connecting Sparsely Distributed Similar Bloggers", ICDM'09, Dec, 2009. pdf [110]
  • Lei Tang, Xufei Wang, and Huan Liu. "Uncovering Groups via Heterogeneous Interaction Analysis", ICDM'09, Dec, 2009. pdf
  • Lei Tang and Huan Liu. "Scalable Learning of Collective Behavior based on Sparse Social Dimensions", The 18th ACM Conference on Information and Knowledge Management (CIKM'09), Hong Kong, Nov. 2-6, 2009. pdf
  • Sai T. Moturu, Jian Yang, and Huan Liu. "Quantifying Utility and Trustworthiness for Advice Shared on Online Social Media", Symposium on Social Intelligence and Networking, IEEE International Conference on Social Computing (SocialCom'09), Vancouver, Canada, Aug 29-31, 2009. pdf
  • Sai T. Moturu and Huan Liu, "Evaluating the Trustworthiness of Wikipedia Articles through Quality and Credibility", The 5th International Symposium on Wikis and Open Collaboration, Florida, Oct 25-27, 2009. pdf
  • Z. Zhao, L. Sun, S. Yu, H. Liu, J. Ye. "Multiclass Probabilistic Kernel Discriminant Analysis", IJCAI'09. pdf [105]
  • L. Tang and H. Liu. "Relational Learning via Latent Social Dimension", Poster Paper, The 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'09), Paris, France, August 2009. pdf data and code
  • N. Agarwal, H. Liu, S. Murthy, A. Sen, X. Wang. "A Social Identity Approach to Identify Familiar Strangers in a Social Network", Third International Conference on Weblogs and Social Media (ICWSM09), Full Paper, May 17 - 20, 2009, San Jose, California. pdf, video
  • Nitin Agarwal, Shamanth Kumar, Huan Liu, Mark Woodward. "BlogTrackers: A Tool for Sociologists to Track and Analyze Blogosphere", Third International Conference on Weblogs and Social Media (ICWSM09), Demo Paper, May 17 - 20, 2009, San Jose, California. pdf
  • R. Zafarani, H. Liu. "Connecting Corresponding Identities across Communities", Third International Conference on Weblogs and Social Media (ICWSM09), Poster Paper, May 17 - 20, 2009, San Jose, California. pdf
  • N. Agarwal, H. Liu, J. Salerno, and S. Sundararajan. "Understanding Group Interaction in Blogosphere: A Case Study", Second International Conference on Computational Cultural Dynamics (ICCCD08), pp 9 - 17. September 15-16, 2008.University of Maryland, College Park, Maryland. pdf. [100]
  • L. Tang, H. Liu, J. Zhang, and Z. Nazeri. "Community Evolution in Dynamic Multi-Mode Networks", KDD'08: 677 - 685. pdf.
  • Z. Zhao, J. Wang, H. Liu, J. Ye, and Y. Chang. "Identifying Biologically Relevant Genes via Multiple Heterogeneous Data Sources", KDD'08: 839 - 847. pdf.
  • S. T. Moturu, H. Liu, and W. Johnson. "Trust Evaluation in Health Information on the World Wide Web", IEEE Engineering in Medicine and Biology Conference (EMBC '08), August 20 - 24, 2008. Vancouver, Canada. pdf.
  • S. Subramanya, B. Li, and H. Liu. "Robust Integration of Multiple Information Sources by View Completion"', IEEE International Conference on Information Reuse and Integration 2008 (IEEE IRI), pp 398-403, July 13 -15, 2008. Las Vegas, Nevada. pdf
  • N. Agarwal, M. Galan, H. Liu, S. Subramanya. "Clustering Blogs with Collective Wisdom", 8th International Conference on Web Engineering (ICWE08), pp 336 - 339. July 14-18, 2008. Yorktown Heights, NY. pdf (short paper). [95]
  • W.K. Wong, D. W.L. Cheung, E. Hung, and H. Liu. "Protecting Privacy in Incremental Maintenance for Distributed Association Rule Mining", Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp 381-392. May 22 - 23, 2008. Osaka, Japan. pdf.
  • N. Agarwal, H. Liu, L. Tang, and P. Yu. "Identifying Influential Bloggers in a Community", First International Conference on Web Search and Data Mining (WSDM08), pp 207-218, February 11-12. Stanford, California. pdf, video available.
  • S. Moturu, H. Liu, and W. Johnson. "Healthcare Risk Modeling for Medicaid Patients", International Conference on Healthcare Informatics, Best Student Paper Award, pp 126-133. January 28-31, 2008. Madeira, Portugal. pdf.
  • S. Moturu, W. Johnson, and H. Liu. "Predicting Future High-Cost Patients: A Real-World Risk Modeling Application”, IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2007), pp 202-208. San Jose, CA, Nov 2-4, 2007. pdf.
  • N. Agarwal, H. Liu, J. Salerno, and P. Yu. ``Searching for `Familiar Strangers’ on Blogosphere: Problems and Challenges”, NSF Symposium on Next-Generation Data Mining and Cyber-enabled Discovery and Innovation. October 10-12, Baltimore, MD. pdf. [90]
  • G.P.C. Fung, J.X. Yu, H. Liu, P.S. Yu: Time-dependent event hierarchy construction. KDD 2007: 300-309
  • J. Chen, Z. Zhao, J. Ye, Huan Liu: Nonlinear adaptive distance metric learning for clustering. KDD 2007: 123-132
  • Z. Zhao and H. Liu. ``Spectral Feature Selection for Supervised and Unsupervised Learning''. International Conference on Machine Learning (ICML-07), June 20-24, 2007, Corvallis, Oregon. pdf.
  • J. Ye, Z. Zhao, and H. Liu. ``Adaptive Distance Metric Learning for Clustering”. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR-07), June 18-23, 2007, Minneapolis, Minnesota.
  • Z. Zhao and H. Liu. ``Semi-supervised Feature Selection via Spectral Analysis", SIAM International Conference on Data Mining (SDM-07), April  26-28, 2007, Minneapolis, Minnesoda. pp641 - 646 pdf. [85]
  • Z. Zhao and H. Liu. ``Searching for Interacting Features", The 20th International Joint Conference on AI (IJCAI-07), January 6-12 Hyderabad, India. pp 1150 - 1155. pdf. Software available.
  • Gabriel P.C. Fung, J. Yu, H. Wang, D.W. Cheung, and H. Liu. ``A Balanced Ensemble Approach to Weighting Classifiers for Text Classification", IEEE International Conference on Dadta Mining (ICDM'06). December 18-22, Hong Kong. pdf.
  • L. Tang, J. Zhang, and H. Liu. ``Acclimatizing Taxonomic Semantics for Hierarchical Content Classification", The 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2006), August, 2006. Philadelphia. pdf.
  • Surendra K. Singhi and H. Liu. ``Feature Subset Selection Bias for Classification Learning", The 23rd International Conferece on Machine Learning (ICML), June, 2006. Pittsburgh, Pennsylvania. pp 849 - 856. pdf.
  • Ping Wu, Ji-Rong Wen, H. Liu, Wei-Ying Ma. ``Query Selection Techniques for Efficient Crawling of Structured Web Sources'',  The 22nd International Conference on Data Engineering (ICDE), Atlanta, Georgia, 2006. pdf. [80]
  • Lei Tang and H. Liu. ``Bias Analysis in Text Classification for Highly Skewed Data", The Fifth IEEE International Conference on Data Mining (ICDM), November, 2005. New Orleans, Louisian. pdf.
  • Surendra Singhi and H. Liu. "Error-Sensitive Grading for Model Combination", Proceedings of the European Conference on Machine Learning (ECML/PKDD). pp 733-740, October, 2005. Porto, Portugal. pdf
  • Nitin Agarwal, Ehtesham Haque, Huan Liu, Lance Parsons. "Research Paper Recommender System: A Subspace Clustering Approach", The 6th International Conference on Web-Age Information Management (WAIM 2005), pp. 475 - 491, October 11-13, 2005, Hang Zhou, China. pdf.
  • R. Jin, H. Liu. "A Novel Approach to Model Generation for Heterogeneous Data Classification", the 19th International Joint Conference on AI  (IJCAI-05), July 30 - August 5, 2005. Edinburgh, Scotland. online proceedings
  • R. Jin, H. Liu, K. Feng. "Learning with Labeled Sessions", the 19th International Joint Conference on AI  (IJCAI-05), July 30 - August 5, 2005. Edinburgh, Scotland. online proceedings [75]
  • J. Sun, H. Zeng, H. Liu, Y. Lu, Z. Chen. "CubeSVD: A Novel Approach to Personalized Web Search", the 14th International World Wide Web Conference (WWW2005), May 10- 14, Chiba, Japan.
  • K. Torkkola, S. Venkatesan, and H. Liu. "Sensor Sequence Modeling for Driving", the 18th International FLAIRS Conference, May 15-17, 2005, Clearwater Beach, Florida. pdf
  • M. Galan, H. Liu, K. Torkkola.  “Intelligent Instance Selection of Data Streams for Smart Sensor Applications”, SPIE Defense & Security Symposium, Intelligent Computing: Theory and Applications III, Orlando, Florida, March 28-29, 2005. Volume 5803. pp. 108 - 119. pdf
  • Lei Yu, Chitta Baral, Seungchan Kim, Jessica L Rennert, Dominique Hoelzinger, Michael E Berens, and Huan Liu. "Discriminative Gene Selection for Brain Tumor Migration". Pacific Symposium on Biocomputing (PSB), 2005. (poster)
  •  D. Banks, G. Dong, H. Liu, and A. Mandvikar. "Teaching Undergraduate Data Mining in Engineering Program", Frontiers in Educations Conference, October 20-23, 2004, Savannah, Georgia. pdf from FIE04 or draft pdf
  • K. Torkkola, S. Venkatesan, and H. Liu. "Sensor Selection for Maneuver Classification", The 7th IEEE International Conference on Intelligent Transportation Systems (ITSC2004), October 3-6, 2004, Loews L'Enfant Plaza Hotel, Washington DC. pdf [70]
  • R. Jin and H. Liu. "SWITCH: A Novel Approach to Ensemble Learning for Heterogeneous Data", The 15th European Conference on Machine Learning, September 20-24, 2004, Pisa, Italy. pdf
  • L. Yu and H. Liu. "Redundancy Based Feature Selection for Microarry Data", SIGKDD, KDD 2004, August, 22 - 25, 2004. Seattle, Washington. pdf
  • H. Liu, A. Mandvikar, and J. Mody. "An Empirical Study of Building Compact Ensembles for Classification", The Fifth International Conference on Web-Age Information Management (WAIM), 15 - 17 July 2004, Dalian, China. pdf
  • R. Jin and H. Liu. "Robust Feature Construction for Support Vector Machines", International Conference on Machine Learning, 4 - 8 July, 2004, Banff, Alberta, Canada. pdf
  • A. Mandvikar, H. Liu, and H. Motoda. "Compact Dual Ensemble for Active Learning", The Eighth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) May 26 - 28, 2004, Sydney, Australia. pdf [65]
  • A. Mandvikar and H. Liu. "Class-Specific Ensembles for Active Learning in Digital Imagery", SIAM International Conference on Data Mining 2004, April 22-24, 2004. pp 412-421. Lake Buena Vista, Florida. pdf
  • P. Foschi, D. Kolippakkam, and H. Liu, "Feature Selection for Image Data via Learning", IMMCN 2003, September 26-30, 2003. pp 1299-1302. (Invited) North Carolina, USA. ps
  • L. Yu and H. Liu, "Efficiently Handling Feature Redundancy in High-Dimensional Data". In Proceedings of The Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, D.C. pp 685-690. August 24 - 27, 2003. pdf. Software available.
  • L. Yu and H. Liu. "Feature Selection for High-Dimensional Data: A Fast Correlation-Based Filter Solution". In Proceedings of The Twentieth International Conference on Machine Leaning (ICML-03), Washington, D.C. pp. 856-863. August 21-24, 2003. pdf [60]
  • H. Liu, A. Mandvikar, P. Foschi, and K. Torkkola, "Active Learning with Ensembles for Image Mining", International Joint Conference on AI (IJCAI'2003). Acapulco, Mexico. pp. 1435-1436. August 9-15, 2003. ps
  • H. Liu, H. Lu, and L. Yu, "Active Sampling: An effective Approach to Feature Selection", SIAM International Conference on Data Mining, pp. 244-248. San Francisco, May, 2003. ps
  • H. Liu, L. Yu, M. Dash, and H. Motoda, "Active Feature Selection Using Classes", PAKDD03, Seoul, Korea. pp. 474-485. April 30 - May 2, 2003. ps
  • S.S. Yau, H. Liu, D. Huang, Y. Yao, Situation-aware personalized information retrieval for mobile Internet, Proceedings of the 27th Annual International Conference on Computer Software and Applications Conference, 2003. COMPSAC 2003,  3-6 Nov. 2003
  • H. Nguyen, P. Velamuru, D. Kolippakkam, H. Davulcu and H. Liu, "Mining `Hidden Phrase' Definitions from the Web", Proceedings of The Fifth Asia Pacific Web Conference, 27-29 Sept., 2003. pp. 156 - 165. Xi'an China. [55] pdf
  • D. Manoranjan, K. Choi, P. Scheuermann, H. Liu, "Feature Selection for Clustering - A Filter Solution", Proceedings of ICDM 2002. Dec 9 - 12, 2002, p. 115-122, Japan. postscript.
  • H. Liu, H. Motoda, and L. Yu, "Feature Selection with Selective Sampling", Proceedings of the 19th International Conference on Machine Learning. July 8-12, 2002. Sydney, p. 395-402, Australia. postscript.
  • W.M. Campbell and H. Liu, "Using Feature Transformation and Selection with Polynomial Networks," Proceedings of the SPIE - The International Society for Optical Engineering vol.4390 p.175-86. Publisher: SPIE-Int. Soc. Opt. Eng. Applications and Science of Computational Intelligence IV. Orlando, Florida, April 16-20, 2001. pdf
  • M. Dash, K. L. Tan, and H. Liu: "Efficient Yet Accurate Clustering". (ICDM-2001), IEEE International Conference on Data Mining, November 2001. pp 99--106.
  • B. Gu, B. Liu, F. Hu, and H. Liu, "Efficiently Determining the Starting Sample Size for Progressive Sampling", Proceedings of the 12th European Conference on Machine Learning, Machine Learning: ECML-2001, L. De Raedt, P. Flach (Eds.) Sept 3 - 7, 2001. Freiburg, Germany. pp 192--202, Springer-Verlag. [50] pdf.
  • B. Gu, F. Hu, H. Liu, "Modeling Classification Performance for Large Data Sets", WAIM'2001, Proceedings of the Second International Conference of Web-Age Information Management, Xi'an, China. July, 2001. pp 317--328. postscript.
  • C. Wen, H. Liu, W.X. Wen, J. Zheng, "A Distributed Hierarchical Clustering System for Web Mining", WAIM'2001, Proceedings of the Second International Conference of Web-Age Information Management, Xi'an, China. Jyly, 2001. pp 103--113. postscript.
  • M. Dash, H. Liu, and X. Xu, "'1 + 1 > 2': Merging Distance and Density Based Clustering", the 7th International Conference on Database Systems for Advanced Applications, DASFAA 2001, pages 32-39, HongKong. IEEE Computer Society Publisher. April, 2001. postscript.
  • M. Dash and H. Liu, "Efficient Hierarchical Clustering Algorithms using Partially Overlapping Partitions", the 5th Pacific Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2001, HongKong. April 2001. pp 495--506. postscript.
  • D.P. Makawita, K.L. Tan, and H. Liu, "Sampling from Databases Using B+ Trees", Conference on Information and Knowledge Management (CIKM 2000), pp 158 -- 164, Washington, DC, November 6-11, 2000 [45]. postscript.
  • F. Hussain, H. Liu, E. Suzuki, and H. Lu, "Exception Rule Mining with a Relative Interestiness Measure", pp 86 -- 97, PAKDD 2000, Kyoto, Japan. April, 2000. Springer. postscript.
  • M. Dash, H. Liu and H. Motoda, "Consistency Based Feature Selection", pp 98 -- 109, PAKDD 2000, Kyoto, Japan. April, 2000. Springer. postscript.
  • M. Dash and H. Liu, "Feature Selection for Clustering", pp 110 -- 121, PAKDD 2000, Kyoto, Japan. April, 2000. Springer. ( ``the Most Influential Paper" award 10 years later at PAKDD 2010) postscript, pdf.
  • N.A. Syed, H. Liu, and K.K. Sung, "A Sudy of Support Vectors on Model Independent Example Selection", International Conference on Knowledge Discovery & Data Mining (KDD'99), pp 272--276, August 15-18, 1999, San Diego, CA, USA. postscript.
  • N.A. Syed, H. Liu, and K.K. Sung, "Handling Concept Drifts in Incremental Learning with Support Vector Machines", International Conference on Knowledge Discovery & Data Mining (KDD'99), pp 317--321, August 15-18, 1999, San Diego, CA, USA. postscript[40].
  • K. Chen and H. Liu "Towards an Evolutionary Algorithm: A Comparison of Two Feature Selection Algorithms", Congress on Evolutionary Computation, pp 1309--1313, July 6-9, 1998, Washington D.C., USA. postscript.
  • H. Liu, H. Lu, L. Feng, and F. Hussain, "Efficient Search of Reliable Exceptions", Proceedings of The Third Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD'99), Beijing, China, pp 194--204, April 26-28, 1999. Springer-Verlag. postscript.
  • H. Liu and R. Setiono, "Feature Transformation and Multivariate Decision Tree Induction", Proceedings of The First International Conference on Discovery Science (DS'98), Fukuoka, Japan December 14-16, 1998. pp 279--290, Springer-Verlag. postscript.
  • M. Dash, H. Liu, "Hybrid Search of Feature Subsets", PRICAI'98, 22-27 November, 1998. Singapore. pp 238-249, Springer-Verlag. postscript.[35]
  • R. Setiono and H. Liu, ``Framentation Problem and Automated Feature Construction'', Proceedings of the 10th IEEE International Conference on Tools with AI (ICTAI'98), pp 208--215, November 10-12, 1998. Taipei, Taiwan. IEEE Computer Society. postscript.
  • K.S. Ng, H. Liu, and H.B. Kwah, ``A Data Mining Application: Customer Retention'', Proceedings ACM-SIGMOD International Conference on Management of Data (SIGMOD'98), June 1-4, 1998. Seattle, Washington, USA.
  • H. Liu, H. Motoda, and M. Dash, ``A Monotonic Measure for Optimal Feature Selection'', 10th European Conference on Machine Learning (ECML-98), April 21-24, 1998. Chemnitz, Germany. pp 101--106, Springer-Verlag. postscript.
  • H. Liu, H. Lu, and J. Yao, ``Identifying Relevant Databases for Multidatabase Mining'', the 2nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'98), April 15-18, 1998. Melbourne, Australia. pp 210--221, Springer-Verlag. postscript.
  • H. Liu and R. Setiono, ``Scalable Feature Selection for Large Sized Databases'', the Fourth World Congress on Expert Systems (WCES'98), March 1998, Mexico City, Mexico. pp 521--528. postscript.
  • M. Dash, H. Liu, and J. Yao, ``Dimensionality Reduction of Unsupervised Data'', the Ninth IEEE International Conference on Tools with AI (ICTAI'97), Nov., 1997, Newport Beach, California. postscript. [30]
  • R. Setiono and H. Liu, ``NeuralLinear: A System for Extracting Oblique Decision Rules from Neural Networks'', the 9th European Conference on Machine Learning (ECML'97), 23-26 April, 1997. Prague, Czech Republic. postscript.
  • J. Yao and H. Liu, ``Searching Multiple Databases for Interesting Complexes'', the 1st Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'97), 23-24 Feb., 1997, pp. 198-210. Singapore. postscript.
  • H. Liu and R. Setiono, ``A probabilistic approach to feature selection - A filter solution'', the 13th International Conference on Machine Learning (ICML'96), July 1996, pp. 319-327. Bari, Italy. postscript.
  • H. Liu and R. Setiono, ``Feature selection and classification - A probabilistic wrapper approach'', the 9th International Conference on Industrial & Engineering Applications of Artificial Intelligence & Expert Systems'' (IEA-AIE'96), June 1996, pp. 419-424. Fukuoka, Japan. postscript.
  • H. Liu and R. Setiono, ``Chi2: Feature selection and discretization of numeric attributes'', the 7th IEEE International Conference on Tools with Artificial Intelligence (TAI'95), Nov.1995, pp. 388-391. Washington D.C., USA. postscript. [25]
  • H. Liu and S.T. Tan, ``X2R: A Fast Rule Generator'', IEEE International Conference on Systems, Man and Cybernetics (SMC'95), Oct. 1995, pp. 631-1635. Vancouver, Canada. postscript.
  • H. Lu, R.Setiono and H. Liu, ``NeuroRule: A Connectionist Approach to Data Mining'', International Conference on Very Large Databases (VLDB'95), Oct. 1995, Zurich, Switzerland. postscript.
  • R. Setiono and H. Liu, ``Understanding Neural Networks via Rule Extraction'', International Joint Conference on Artificial Intelligence (IJCAI-95), Aug. 1995, Montreal, Canada . postscript, pdf
  • W.X. Wen and H. Liu, ``A Feature Weighting Method for Inductive Learning'', The 3rd Pacific Rim International Conference on Artificial Intelligence, August 15-18, 1994, Beijing, China. pp 338-344
  • H. Liu and W.X. Wen, ``Concept Learning through Feature Selection'', First Australian and New Zealand Conference on Intelligent Information Systems, 1-3 December, 1993, Perth, Western Australia. [20]
  • W.X. Wen, H. Liu and A. Jennings, ``Supervised Learning for Self-Generating Neural Trees'', 1993 World Congress on Neural Networks, Portland, Oregon, USA.
  • W.X. Wen, H. Liu and A. Jennings, ``Learning a Neural Tree'', the International Joint Conference on Neural Networks, IJCNN'92, November 3-6, 1992, Beijing, China. pp II-751 - II-756
  • W.X. Wen, A. Jennings and H. Liu, ``A Performance Analysis of Self-Generating Neural Trees'', ibid. pp II-283 - II-288
  • H. Liu, C. Rowles and C. Leckie, ``Evolving a Design'', the First Singapore International Conference on Intelligent Systems, Sept. 28-Oct. 2, 1992, Singapore. pp 337 - 342
  • ``Joint Concept Formation and Abstraction'', (with W. Wen), the Pacific Rim International Conference on Artificial Intelligence, September 15-18, 1992, Seoul, South Korea. [15]
  • ``Planning with Intentions'', (with C. Rowles and G.A. Bekey), ibid.
  • ``Self-Generating Neural Networks and Their Applications to Telecommunications'', (with W. Wen and A. Jennings), the International Conference on Communication Technology, September 16-18, 1992, Beijing, China.
  • ``Self-Generating Neural Networks'', (with W. Wen and A. Jennings), the International Joint Conference on Neural Networks, June 7-11, 1992, Baltimore, U.S.A. pp IV-779 - IV-784.
  • ``Design, Evaluation and Redesign - Handling the ad-hocness of a knowledge-based design system'', (with C.D. Rowles and W. Wen), the IEEE Conference on AI Applications, March 1992, California, U.S.A.
  • ``Knowledge-based Models of Human and Robot Grasping'', (with G.A. Bekey, T. Iberall and R. Tomovic), IFAC Symposium on Systems Identification, July, 1991, Budapest, Yugoslavia. [10]
  • ``Automating the Design of Telecommunication Distribution Networks'', (with C. Rowles, C. Leckie and W. Wen), the First International Conference on Artificial Intelligence in Design, 25-27 June, 1991, Edinburgh, UK.
  • ``Optimizing Knowledge-based Systems Design'', (with W. Wen and C.D. Rowles), the IEEE Conference on AI Applications, February, 1991, Miami, Florida, U.S.A.
  • ``Intention Attributes in Planning'' (with C.D. Rowles), the Pacific Rim International Conference on Artificial Intelligence'90, November, 1990, Nagoya, Japan.
  • ``Integrating Design Principles in Automated Layout Design'' (with C.D. Rowles and C. Leckie), the International Conference on Automation, Computer Vision and Robotics, September, 1990, Singapore. pp 180 - 184
  • ``The Multi-dimensional quality of task requirements for dextrous robot hand control'' (with T. Iberall and G.A. Bekey), the IEEE International Conference on Robotics and Automation, May, 1989, Scottsdale, Arizona. [5]
  • ``Building a generic architecture for robot hand control'' (with T. Iberall and G.A. Bekey), the IEEE International Conference on Neural Networks, July, 1988, San Diego, California.
  • ``Robot hand-eye coordination: shape description and grasping'', (with K. Rao, G. Medioni and G.A. Bekey) the IEEE International Conference on Robotics and Automation, April, 1988, Philadelphia, Pennsylvania.
  • ``Reasoning about grasping from task description'' (with T. Iberall and G.A. Bekey), Advances in Intelligent Robotics Systems, SPIE's Cambridge Symposium on Optical and Optoelectronic Engineering, November, 1988, Cambridge, Massachusetts.
  • ``Learning activities in robot hand control'' (with G.A. Bekey), the Robotics and Automation Symposium, the International Association of Science and Technology for Development, May, 1987, Santa Babra, California.

 

Patents

Journals and Magazines

Conference Patent Journal Workshop Book

  • Junrui Liu, Tong Li, Zhen Yang, Di Wu, and Huan Liu. ``Fusion Learning of Perference and Bias from Ratings and Reviews for Item Recommendation", Data & Knowledge Engineering, Vol. 150, March, 2024. https://doi.org/10.1016/j.datak.2024.102283

2023

  • Kaize Ding, Elnaz Nouri, Guoqing Zheng, Huan Liu, and Ryen White. ``Toward Robust Graph Semi-Supervised Learning against Extreme Data Scarcity", IEEE Transactions on Neural Networks and Learning Systems, Forthcoming
  • Amrita Bhattacharjee and Huan Liu. ``Fighting Fire with Fire: Can ChatGPT Detect AI-generated Text?", SIGKDD explorations, December 2023, Volume 25, Issue 1.
  • Haiyang Y, Runtong Xu, Hui Zhang, Zhen Yang, and Huan Liu. ``EV-FL: Efficient Verifiable Federated Learning with Weighted Aggregation for Industrial IoT Networks", IEEE/ACM Transactions on Networking, Forthcoming
  • Kaize Ding, Jianling Wang, Jundong Li, James Caverlee, and Huan Liu. ``Robust Graph Meta-learning for Weakly-supervised Few-shot Node Classificatio", ACM TKDD, Forthcoming
  • Zhe Xu, Kaize Ding, Yu-Xiong Wang, Huan Liu, Hanghang Tong. ``Generalized Few-Shot Node Classification: Towards an Uncertainty-Based Solution", Knowledge and Information Systems, Springer Nature. Forthcoming
  • Garima Agrawal, Dimitri Bertsekas, Huan Liu. ``Auction-Based Learning for Question Answering over Knowledge Graphs", Artificial Intelligence Section, Journal of Information, MDPI. Forthcoming
  • Shisong Yang, Yuwen Chen, Zhen Yang, Bowen Li, and Huan Liu. ``Fast Secure Aggregation with High Dropout Resilience for Federated Learning” , IEEE Transactions on Green Communications and Networking ( Volume: 7, Issue: 3, September 2023) , pp: 1501-1514. May 17, 2023. DOI: 10.1109/TGCN.2023.3277251
  • Paras Sheth, Ruocheng Guo, Lu Cheng, Huan Liu, and Selcuk Candan. ``Causal Disentanglement for Implicit Recommendations with Network Information", ACM TKDD, Volume 17, Issue 7, Article No.: 94, pp 1-18. Aprial 6, 2023. https://dl.acm.org/doi/10.1145/3582435,
  • Qianru Wang, Bin Guo, Lu Cheng, Zhiwen Yu, Huan Liu. ``CausalSE: Understanding Varied Spatial Effects with Missing Data Towards Adding New Bike-sharing Stations", ACM Trans. on Knowledge Discovery in Data (TKDD). Online:17 May 2022; published: 17(2), article no. 20. pp 1-24. 20 March 2023. https://doi.acm.org?doi=3536427

2022

 

2021

2020

2019

2018

2017

  • Kai Shu, Amy Sliva, Suhang Wang, Jiliang Tang, and Huan Liu. ``Fake News Detection on Social Media: A Data Mining Perspective", SIGKDD Explorations, 19(1):22-36, June, 2017. pdf [105]
  • Tahora H. Nazer, Guoliang Xue, Jiyu Sheng, and Huan Liu. ``Intelligent Disaster Response via Social Media Analysis - A Survey", SIGKDD Explorations, 19(1):46-59, June, 2017. pdf
  • Suhas Ranganath, Xia B Hu, Jiliang Tang, Suhang Wang, and Huan Liu. ``Understanding and Identifying Rhetorical Questions in Social Media", ACM Transcation on Intelligent Systems and Technology (TIST). Forthcoming. pdf
  • Yun Li, Tao Li, and Huan Liu. ``Recent Advances in Feature Selection and Its Applications", Springer, Knowledge and Information Systems (KAIS). pp 1-27, May 2017. DOI 10.1007/s10115-017-1059-8. 
  • Suhas Ranganth, Suhang Wang, Xia Hu, Jiliang Tang, and Huan Liu. ``Facilitating Time Critical Information Seeking in Social Media", IEEE Trans on Knowledge and Data Engineering (TKDE). Forthcoming. pdf
  • Fred Morstatter and Huan Liu. ``Discovering, Assessing, and Mitigating Data Bias in Social Media", Elsevier Journal of Online Social Networks and Media.  Volume 1, Pages: 1-13. June 2017. pdf [100]
  • Fred Morstatter, Liang Wu, Uraz Yavanoglu, Stephen S. Corman, and Huan Liu. ``Identifying Framing Bias in Online News", ACM Transactions on Social Computing (TSC). Forthcoming. pdf
  • Jundong Li and Huan Liu. ``Challenges of Feature Selection for Big Data Analytics", Special Issue on Big Data, IEEE Intelligent Systems. 32 (2), 9-15. 2017
  • Feng Xia, Wei Wang, Teshome Megersa Bekele, and Huan Liu. ``Big Scholarly Data: A Survey", IEEE Trans on Big Data, Issue:99, Page(s): 1. January 2017. DOI: 10.1109/TBDATA.2016.2641460.

2016

2015

2014

  • Pritam Gundecha , Geoffrey Barbier, Jiliang Tang, and Huan Liu. ``'User Vulnerability and its Reduction on a Social Networking Site'', ACM Transactions on Knowledge Discovery from Data (TKDD). 9(2): Pages 12:1-12:25, 2014. pdf
  • Jiliang Tang and Huan Liu.``An Unsupervised Feature Selection Framework for Social Media Data'', IEEE Transactions on Knowledge and Data Engineering (TKDE). 26(12): 2914-1927, 2014. pdf [75]
  • Kathleen M. Carley, Jürgen Pfeffer, Fred Morstatter, Huan Liu. ``Embassies burning: toward a near-real-time assessment of social media using geo-temporal dynamic network analytics" Social Netw. Analys. Mining 4(1) (2014)
  • Jiliang Tang and Huan Liu. ``Feature Selection for Social Media Data", ACM Transactions on Knowledge Discvoery from Data (TKDD). 8(4) Pages 19:1 - 19:27, 2014. pdf
  • Zhi-Dan Zhao, Zi-Gang Huang, Liang Huang, Huan Liu, Ying-Cheng Lai. ``Scaling and correlation of human movements in cyberspace and physical space", Physical Review E 90 (5), 050802.
  • Reza Zafarani and Huan Liu. ``Behavior Analysis in Social Media", IEEE Intelligent Systems, 29(4): 9-11, 2014. pdf
  • Xinwang Liu, Lei Wang, Jian Zhang, Jianping Yin, and Huan Liu, ``Global and Local Structure Preservation for Feature Selection", IEEE Transactions on Neural Networks and Learning Systems. 25(6): 1083-1095, 2014. pdf [70]
  • Dror Y. Kenett, Fred Morstatter, H. Eugene Stanley, and Huan Liu. ``Discovering Social Events through Online Attention", PLOS ONE, July 2014. paper access
  • Shamanth Kumar, Fred Morstatter, and Huan Liu. ``Monitoring Social Media for Humanitarian Assistance and Disaster Relief", invited contribution, IEEE Special Technical Community Social Networking, STCSN E-Letter Vol. 2 No. 1, March 12, 2014.
  • Shijin Li, Jianbin Qiu, Xinxin Yang, Huan Liu, DingshengWan, Yuelong Zhu: A novel approach to hyperspectral band selection based on spectral shape similarity analysis and fast branch and bound search. Eng. Appl. of AI 27: 241-250 (2014)
  • Lei Wang, Luping Zhou, Chunhua Shen, Lingqiao Liu, Huan Liu: A Hierarchical Word-Merging Algorithm with Class Separability Measure. IEEE Trans. Pattern Anal. Mach. Intell. 36(3): 417-435 (2014)

2013

  •  Jiliang Tang, Yi Chang, and Huan Liu. ``Mining Social Media with Social Theories: A Survey", SIGKDD explorations, 15(2): 20 - 29. December 2013. pdf [65]
  • Jiliang Tang, Xia Hu, and Huan Liu, ``Social Recommendation: A Review", Journal of Social Network Analysis and Mining, Springer. 3(4): 1113-1133 (2013). pdf, online first
  • Xufei Wang, Lei Tang, Huan Liu, and Lei Wang, ``Learning with Multi-resolution Overlapping Communities", Knowledge and Information Systems (KAIS), Springer, Volumen 36, Issue 2 (2013): 517-535. pdf
  • Zheng Zhao, Lei Wang, Huan Liu, and Jieping Ye. ``On Similarity Preserving Feature Selection", IEEE Transactions on Knowledge and Data engineering (TKDE), 25(3): 619-632, 2013. pdf

2012

  • Geoffrey Barbier, Reza Zafarani, Huiji Gao, Gabriel Fung, and Huan Liu. ``Maximizing Benefits from Crowdsourced Data", Special Issue: Data Model, Computational and Mathematical Organization Theory, 18(3): 257-279,2012. DOI: 10.1007/s10588-012-9121-2. pdf
  • Lei Tang, Xufei Wang and Huan Liu. "Scalable Learning of Collective Behavior". IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 24, no. 6, pp. 1080-1091, June, 2012. Selected as a June-2012 featured article by the Special Technical Community on Social Networks, IEEE Computer Societypdf [60]
  • Nitin Agarwal, Huan Liu, Lei Tang, and Philip Yu. "Modeling Blogger Influence in a Community", Social Network Analysis and Mining, Springer,  2(2): 139-162, 2012. DOI: 10.1007/s13278-011-0039-3. pdf
  • Fred Morstatter, Huan Liu, and Daniel Zeng. Opening Doors to Sharing Social Media Data, IEEE Intelligent Systems, January/February 2012. Vol.27, No. 1: pp 47 -51. (selected as a May-2012 feature article by the Special Technical Community on Social Networks, IEEE Computer Society)
  • Jiliang Tang, Xufei Wang, Huiji Gao, Xia Hu & Huan Liu. "Enriching Short Text Representation in Microblog for Clustering", Frontiers of Computer Science in China, Vol. 6, Issue 1:88-101, 2012. DOI: 10.1007/s11704-011-1167-7.
  • Lei Tang, H. Liu and J. Zhang. "Identifying Evolving Groups in Dynamic Multi-Mode Networks". IEEE Transactions on Knowledge and Data Engineering (TKDE), 24(1): 72-85, 2012. pdf.  
  • Lei Tang, Xufei Wang, and Huan Liu. "Group Profiling for Understanding Social Structures", ACM Transaction on Intelligent Systems and Technology, 3(1):15 2012. pdf [55]

2011

  • Lei Tang, Xufei Wang, and Huan Liu. "Community Detection via Heterogeneous Interaction Analysis", Data Mining and Knowledge Discovery, Springer. August, 2011. DOI: 10.1007/s10618-011-0231-0. pdf
  • Geoffrey Barbier, Lei Tang and Huan Liu. "Understanding Online Groups through Social Media". WIREs Data Mining and Knowledge Discovery, May 20, 2011.
  • N. Yagnik, H. Liu, and H.J.S. Fernando. "Sensor Networks: Decentralized Monitoring and Subspace Classification of Events", Special Issue on Novel Applications of Machine Learning, International Journal of General Systems, Taylor & Francis, Volume 40 Issue 4, 457. May 4, 2011. doi:10.1080/03081079.2010.544882
  • Sai Moturu and Huan Liu. "Quantifying the Trustworthiness of Social Media Content", Journal of Distributed and Parallel Databases, Springer, Volume 29, January 4, 2011. DOI: 10.1007/s10619-010-7077-0.
  • Lei Tang and Huan Liu. "Leveraging Social Media Networks for Classification". Journal of Data Mining and Knowledge Discovery (DMKD), Springer, DOI: 10.1007/s10618-010-0210-x, January 14, 2011.[50]

2010 and earlier

  • L. Tang and H. Liu. "Toward Collective Behavior Prediction via Social Dimension Extraction". IEEE Intelligent Systems, July/August 2010 (vol. 25 no.4), pp. 19--25. pdf, data and code
  • N. Agarwal, M. Galan, H. Liu, and S. Subramanya. "WisColl: Collective Wisdom based Blog Clustering". Journal of Information Science: Special Issue on Collective Intelligence (INS-CI), 180(1):39-61. 2010. http://dx.doi.org/10.1016/j.ins.2009.07.010.
  • S. Moturu, W. Johnson, and H. Liu. "Predictive Risk Modeling for Forecasting High-Cost Patients: a Real-World Application
    Using Medicaid Data", International Journal of Biomedical Engineering and Technology, Special Issue on Warehousing and Mining Complex Data: Applications to Biology, Medicine, Behavior, Health and Environment, 3(1-2): 114-132. 2009. pdf.
  • Z. Zhao and H. Liu. "Searching for Interacting Features in Subset Selection", Intelligent Data Analysis - An International Journal, 13(2): 207 -228, 2009. pdf
  • S. Subramanya, Z. Wang, B. Li, and H. Liu. "Completing Missing Views for Multiple Sources of Web Media", International Journal of Data Mining, Modeling and Management, 1(1):23-44, 2008. [45]
  • N. Agarwal and H. Liu. "Blogosphere: Research Issues, Applications, and Tools", SIGKDD Explorations, 10(1): 18-31, July 2008. related video lecture
  • L. Tang, H. Liu, J. Zhang, N. Agarwal and J.J. Salerno. “Topic Taxonomy Adaptation for Group Profiling”, ACM Transactions on Knowledge Discovery from Data. TKDD 1(4): 1--28 (2008).
  • N. Agarwal, H. Liu, and J. Zhang. ``Blocking Objectional Web Contents by Leveraging Multiple Information Sources". SIGKDD Explorations, pdf, 8(1):17 - 26, June, 2006.
  • N. Agarwal, E. Haque, H. Liu, and L. Parsons. ``A Subspace Clustering Framework for Research Group Collaboration". International Journal of Information Technology and Web Engineering, 1(1), pdf, pp 35 - 58, January - March, 2006
  • K.S. Candan, J.W. Kim, H. Liu, and R. Suvarna. ``Discovering Mappings in Hierarchical Data from Multiple Sources using the Inherent Structure". The Knowledge and Information Systems Journal.  pdf, 10(2): 185-210, August, 2006. [40]
  • M. Berens, H. Liu, L. Parsons, L. Yu, and Z. Zhao. “Fostering Biological Relevance in Feature Selection for Microarray Data”, Trends and Controversies, pdf, pp 71 - 73. November/December 2005, IEEE Intelligent Systems.
  • H. Liu and L. Yu. "Toward Integrating Feature Selection Algorithms for Classification and Clustering", IEEE Trans. on Knowledge and Data Engineeringpdf, 17(4), 491-502, 2005.
  • L. Yu and H. Liu. "Efficient Feature Selection via Analysis of Relevance and Redundancy", Journal of Machine Learning Research, pdf, JMLR 5 (Oct): 1205--1224, 2004.
  • H. Liu, H. Motoda, and L. Yu. "A Selective Sampling Approach to Active Feature Selection", Artificial Intelligence, Elsevier, 159(1-2):49-74, 2004, pdf.
  • P. Foschi and H. Liu. "Active Learning for Detecting a Spectrally Variable Subject in Color Infrared Imagery", Pattern Recognition Letters, Elesevier, pdf,  25(13): 1509-1517, 2004. [35]
  • L. Parson, E. Haque, and H. Liu. "Subspace Clustering for High Dimensional Data - A Review", SIGKDD Explorationspdf, 6(1): 90 - 105, June, 2004.
  • M. Dash and H. Liu. "Consistency-Based Search in Feature Selection", Artificial Intelligence. 151(1-2):155-176, December 2003, pdf.
  • D. Makawita, K-L. Tan, and H. Liu. "Sampling from Databases Using B+Trees", Intelligent Data Analysis, 6(4):359-377, 2002, IPO.
  • M. Dash, H. Liu, P. Scheuermann, and K-L. Tan. "Fast Hierarchical Clustering and Its Validation", Data and Knowledge Engineering, Elsevier Science. 44(1):111-140. Dec, 2002.
  • Z. Chen, F. Lin, H. Liu, W.Y. Ma, Liu Wenyin. "User Intention Modelling in Web Applications Using Data Mining", World Wide Web - Internet and Web Information Systems Journal, Kluwer Academic Publishers. 5(3):181-192. 2002. [30]
  • H. Liu, F. Hussain, C.L. Tan, and M. Dash. "Discretization: An Enabling Technique", Journal of Data Mining and Knowledge Discovery 6(4): 393-423; Oct 2002. pdf. Software available.
  • H. Liu and H. Motoda, "On Issues of Instance Selection", Journal of Data Mining and Knowledge Discovery. 6(2):115-130; Apr 2002.
  • Z. Zhou, H. Liu, S.Z. Li, and C.S. Chua, "Rule Mining with Prior Knowledge - A Belief Networks Approach", Intelligent Data Analysis, 5(2):95-110, 2001. postscript, tar.gz files.
  • K.S. Candan, H. Liu, and R. Suvarna, "Resource Description Framework: Metadata and Its Applications", ACM SIGKDD Explorations, July 2001. 3(1):6-19. pdf.
  • H. Liu, H. Lu, and J. Yao, "Towards Multidatabase Mining: Identifying Relevant Databases", IEEE Transactions on Knowledge and Data Engineering. 13(4):541-553. July/August 2001. postscript[25]
  • K.S. Ng and H. Liu "Customer Retention via Data Mining", Issues on the Application of Data Mining, Artificial Intelligence Review, Kluwer Academic Publishers. 14(6):569-590, December 2000. postscript
  • J. Yao, M. Dash, S.T. Tan and H. Liu, ``Entropy-based Fuzzy Clustering and Fuzzy Modeling'', Fuzzy Sets and Systems - International Journal of Soft Computing and Intelligence, Official Publication of the International Fuzzy System Association, Elsevier. 113(3):381-388, 2000. pdf [20]
  • R. Setiono and H. Liu, ``A Connectionist Approach to Generating Oblique Decision Trees'', IEEE Transactions on Systems, Man, and Cybernetics (Part B: Cybernetics), pp 440--444, Volume 29, Number 3, June 1999.
  • H. Liu and R. Setiono, ``Some Issues on Scalable Feature Selection'', Expert Systems with Application, 15 (1998) Elsevier. Pages 333-339. postscript.
  • H. Liu and R. Setiono, ``Incremental Feature Selection'', Applied Intelligence, Volume 9, Number 3, November/December 1998. Kluwer Academic Publishers. Pages 217-230. postscript.
  • H. Liu and H. Motoda, ``Feature Transformation and Subset Selection'', IEEE Intelligent Systems, March/April 1998, Volume 13, Number 2, Pages 26-28. postscript.
  • R. Setiono and H. Liu, ``Analysis of Hidden Representations by Greedy Clustering'', Connection Science, Vol. 10, No. 1, 1998. Carfax. pages 21-42. postscript.
  • R. Setiono and H. Liu, ``NeuroLinear: from Neural Networks to Oblique Decision Rules'', Neurocomputing, Elsevier, Vol. 17, No. 1, September 1997, pages 1-25. postscript.
  • M. Dash and H. Liu, "Feature Selection for Classification". Intelligent Data Analysis - An International Journal, Elsevier, Vol. 1, No. 3, pages 131 - 156, 1997. postscript.
  • H. Liu and R. Setiono, ``Feature Selection via Discretization of Numeric Attributes'', IEEE Trans. on Knowledge and Data Engineering, VOL.9, NO. 4, July/August 1997. pp. 642-645. postscript. [15]
  • R. Setiono and H. Liu, ``Neural Network Feature Selector'', IEEE Trans. on Neural Networks, Vol. 8, No. 3, May 1997, pp. 654-662. postscript.
  • H. Lu, R. Setiono and H. Liu, ``Effective Data Mining Using Neural Networks'', IEEE Trans. on Knowledge and Data Engineering, Vol. 8, No. 6, Dec. 1996, pp. 957-961. postscript.
  • H. Liu, ``Efficient Rule Induction from Noisy Data'', Expert Systems with Applications: An International Journal, Vol. 10, No. 2, 1996. Pergamon. pp. 275-280. postscript.
  • R. Setiono and H. Liu, ``Symbolic Representation of Neural Networks'', the IEEE Computer, Mar. 1996, pp 71-77. postscript.
  • H. Liu and R. Setiono, ``Dimensionality Reduction via Discretization'', Knowledge-Based Systems, Vol. 9, No. 1, Feb. 1996. Elsevier. pp. 67-72. postscript. [10]
  • R. Setiono and H. Liu, ``Improving Backpropagation Learning with Feature Selection'', Applied Intelligence, Vol. 6, Kluwer Academic Publishers, 1996, pp 129-139. postscript.
  • H. Liu and W.X. Wen, ``Supervised Learning for Self-Generating Neural Networks'', Australian Journal of Intelligent Information Processing Systems, Vol. 2, No. 2, Winter 1995, pp 12-19. postscript.
  • H. Liu, C. Rowles and W. Wen, ``Critics for Knowledge-Based Design Systems'', the IEEE Transactions on Knowledge and Data Engineering, Vol. 7, NO. 5, Oct. 1995, pp 740-750. postscript.
  • H. Liu and W. Wen, ``Joint Concept Formation'', International Journal of Knowledge Acquisition, Vol. 6, 1994, pp 75-87. postscript.
  • G.A. Bekey, H. Liu, R. Tomovic and W.J. Karplus, ``Knowledge-Based Control of Grasping in Robot Hands Using Heuristics from Human Motor Skills'', the IEEE Transactions on Robotics and Automation, Vol.9, No.6, Dec. 1993, pp 709-722. [5]
  • A. Jennings, H. Higuchi and H. Liu, ``A Personal News Service based on a User Model Neural Network'', Australian Telecommunications Research, Vol. 27, No.1, 1993, pp 1-12.
  • A. Jennings, C.Rowles, C. Leckie and H. Liu, ``AI Applications in Telecommunications'', Telecommunications Journal of Australia, Vol. 41, No. 1, 1991, Australia, pp 47-55.
  • H. Liu, T. Iberall and G.A. Bekey, ``Nerual network architecture for robot hand control'', the IEEE Control Systems, April 1989, pp 38-43.
  • K. Rao, H. Liu, G. Medioni and G.A. Bekey, ``Shape description and grasping for robot hand and eye coordination '' the IEEE Control Systems, Feb. 1989, pp 22-29.

International Workshops and Conference Special Sessions

Conference Patent Journal Workshop Book

  • Amrita Bhattacharjee, Raha Moraffah, Joshua Garland, and Huan Liu. ``Towards LLM-guided Causal Explainability for Black-box Text Classifiers", AAAI Workshop on Responsible Language Modes (ReLM2024), AAAI2024. February 26, 2024. Vancouver Canda
  • Mansooreh Karami, David Mosallanezhad, Paras Sheth, and Huan Liu. ``Silence Speaks Volumes: Re-weighting Techniques for Under-Represented Users in Fake News Detection", the DCAI workshop (in conjunction with IEEE ICDM 2023), December 1 - 4, 2023. Shanghai, China.
  • Faisal Alatawi, Paras Sheth and Huan Liu. ``Inside Echo Chambers: An Exploration of Polarization and Topic Diversity on Social Media", Working Paper Track, 16th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS2023), September 22-23, 2023. Pittsburgh, PA.
  • Zeyad Alghamdi, Faisal Alatawi, Mansooreh Karami, Tharindu Kumarage, Ahmadreza Mosallanezhad and Huan Liu. ``Code RED: Reactive Emotion Difference For Stress Detection on Social Media", Working Paper Track, 16th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS2023), September 22-23, 2023. Pittsburgh, PA.
  • Paras Sheth, Ting Liu, Durmus Doner, Yuhang Wei, Qi Deng, Rebecca Muenich, John Sabo, K. Selcuk Candan, and Huan Liu.  ``Causal Discovery for Feature Selection in Physical Process-Based Hydrological Systems", Special Session on MLBD, IEEE International Conference on Big Data (BigData), Dec. 17 - 20, 2022, Osaka, Japan.
  • Paras Sheth, Reepal Shah, John Sabo, K. Selcuk Candan, and Huan Liu. ``STCD: A Spatio-Temporal Causal Discovery Framework for Hydrological Systems", Special Session on MLBD, IEEE International Conference on Big Data (BigData), Dec. 17 - 20, 2022, Osaka, Japan.
  • Anique Tahir, Lu Cheng, Ruocheng Guo, and Huan Liu.  ``Distributional Shift Adaptation using Domain-Specific Features", Special Session on MLBD, IEEE International Conference on Big Data (BigData), Dec. 17 - 20, 2022, Osaka, Japan.
  • Kaize Ding, Jianling Wang, Jundong Li, James Caverlee, and Huan Liu. ``Robust Graph Meta-learning for Weakly-supervised Few-shot Node Classification", the the 1st Workshop on Trustworthy Learning on Graphs (TrustLOG), co-located with the 31st ACM International Conference on Information and KnowledgeManagement (CIKM),  October 17-21, 2022. Atlanta, Georgia. Best Paper Award
  • Kaize Ding, Kai Shu, Yichuan Li Amrita Bhattacharjee, and Huan Liu. “Challenges in Combating COVID-19 Infodemic - Data, Tools, and Ethics”, 5th International Workshop on MiningActionable Insights from Social Networks (MAISoN), co-located with 29th ACM International Conference on Information and KnowledgeManagement (CIKM), October 19-23, 2020. Galway, Ireland.
  • Lu Cheng, Ruocheng Guo, and Huan Liu. ``Robust Cyberbullying Detection with Causal Interpretation". In Proceedings of the WWW'19 CyberSafety Workshop, May 13, San Francisco, CA. pdf
  • Ghazaleh Beigi, Suhas Ranganath, and Huan Liu. ``Signed Link Prediction with Sparse Data: The Role of Personality Information", In the Proceedings of the WWW'19 Women in Web Data Science Workshop (WinDS19), May 13-17, San Francisco, CA. pdf
  • Kai Shu, Suhang Wang, and Huan Liu. Understanding User Profiles on Social Media for Fake News Detection. The First IEEE International Workshop on Fake MultiMedia (FakeMM2018), April 10-12, 2018. Miami, FL.
  • Yafeng Lu, Xia Hu, Feng Wang, Shamanth Kumar, Huan Liu and Ross Maciejewski. Visualizing Social Media Sentiment in Disaster Scenarios. The WWW2015 Workshop on Social Web for Disaster Management (SWDM), May 18, 2015. Florence, Italy.
  • Dror Kenett, Fred Morstatter, Gene Stanley and Huan Liu. Extreme Event Detection in Online Social Media using Social Focus, The 2014 KDD Workshop on Learning about Emergencies from Social Information (KDD-LESI2014), New York, NY. August 24, 2014.
  • Fred Morstatter, Nichola Lubold, Heather Pon-Barry, Jürgen Pfeffer, Huan Liu. Finding Eyewitness Tweets During Crises, ACL Workshop on Language Technology and Computational Social Science, June 2014. Baltimore, Maryland.
  • Shamanth Kumar, Huan Liu, and Fred Morstatter. Social Computing and Information in the New Information Age, presentation, Intelligence in Science. Brussels, Belgium. October 8 -9, 2013
  • Huiji Gao, Jiliang Tang, and Huan Liu. Mobile Location Prediction in a Spatio-Temporal Context. In Workshop on Mobile Data Challenge by Nokia, Pervasive 2012, Newcastle, UK. June 18-22, 2012. Winning the 3rd Place Dedicated Task 2: Next Location Prediction.
  • Lei Tang, Huiji Gao, and Huan Liu. Network Quantification Despite Biased Labels. In Workshop on Mining and Learning with Graphs, KDD 2010.
  • Lei Tang, Xufei Wang, Huan Liu and Lei Wang. A Multi-Resolution Approach to Learning with Overlapping Communities. In Workshop on Social Media Analytics, KDD 2010. pdf
  • Lei Tang and Huan Liu. Uncovering Cross-Dimension Group Structures in Multi-Dimensional Networks, Workshop on Analysis of Dynamic Networks at the SIAM International Conference on Data Mining, 2009. pdf.
  • Zheng Zhao and Huan Liu. Multi-source feature selection via geometry-dependent covariance analysis. Journal of Machine Learning Research, Workshop and Conference Proceedings Volume 4: New challenges for feature selection in data mining and knowledge discovery, 4:36-47, 2008. pdf
  • Shankara Subramanya and Huan Liu. SocialTagger - Collaborative Tagging for Blogs in the Long Tail, Workshop on Search in Social Media, ACM 17th Conference on Information and Knowledge Management, October 26-30, 2008. Napa Valley, California. pdf
  • Payam Refaeilzadeh, Lei Tang, Huan Liu. “On Comparison of Feature Selection Algorithms”, AAAI 2007 Workshop on Evaluation Methods for Machine Learning II, Vancouver, British Columbia, Canada. July 22, 2007. pdf.
  • Prabhdeep Singh, Ravi Bhimavarapu, Hasan Davulcu, Chitta Baral, Seungchan Kim, Huan Liu, Mike Bittner, I.V. Ramakrishnan. "BioLog: A Browser Based Collaboration and Resource Navigation Assistant for BioMedical Researchers", 2nd International Workshop on Data Integration in the Life Sciences (DILS 2005) University of California, San Diego July 20 - 22, 2005.
  • K Selcuk Candan, Jong Wook Kim, Huan Liu, and Reshma Suvarna. "Stucture-based Mining of Hierarchical Media data, Metadata, and Ontologies", Fifth International Workshop on Multimedia Data Mining (MDM/KDD 2004), August 22 - 25, 2004, Seattle, WA, USA. pdf
  • P. Foschi, G. Fields II, and H. Liu. "Detecting a Spectrally Variable Subject in Color Infrared Imagery Using Data-Mining and Knowledge-Engine Methods". 3rd International workshop on Pattern Recognition in Remote Sensing, Kingston University, Kingston upon Thames, August 27, 2004. pdf
  • L. Parson, E. Haque, and H. Liu. "Evaluating Subspace Clustering Algorithms", Workshop on Clustering High Dimensional Data and Its Applications, SIAM International Conference on Data Mining 2004, April 24, 2004. Lake Buena Vista, Florida. pdf
  • Y. Ding, H. Liu, A. Ramineni, A. Sen. "Detecting Hidden Messages in Images: A Comparative Study", 2nd Workshop on Privacy Preserving Data Mining (PPDM), Melbourne, Florida, USA, November 19, 2003. some related publications
  • P. Foschi, D. Kolippakkam, H. Liu, A. Mandvikar, "Feature Extraction for Image Mining", International Workshop on Multimedia Information Systems (MIS 2002), 10/30/02 - 11/1/02. p 103-109. Tempe, Arizona. pdf.
  • P. Foschi and H. Liu, "Active Learning for Classifying a Spectrally Variable Subject", the 2nd International Workshop on Pattern Recognition for Remote Sensing, (PRRS 2002), August 16, 2002. p. 115-124. Niagara Falls, Canada. pdf.
  • B. Gu, B. Liu, F. Hu, and H. Liu, "Efficiently Determining Initial Sample Size for Progressive Sampling", SIGMOD Data Mining and Knolwedge Discovery Workshop, (DMDK), May 20, 2001, Santa Barbra, USA. postscript.
  • D. Manoranjan and H. Liu, "Attribute Hierarchy: A Fast and Memory-Efficient Approach to Density-Based Clustering", ACM SIGKDD Workshop on Distributed and Parallel Knowledge Discovery (DPKD-2000), Boston, August 2000.
  • S.N. Ahmed, H. Liu and K.K. Sung "Incremental Learning with Support Vector Machines" International Joint Conference on Artificial Intelligence (IJCAI99), Workshop on Support Vector Machines, August 2, 1999, Stockholm, Sweden. postscript.
  • M. Dash and H. Liu "Handling Large Unsupervised Data via Dimensionality Reduction", SIGMOD Data Mining and Knolwedge Discovery Workshop, (DMDK), May 30, 1999, Philadelphia, USA.
  • H. Liu, F. Hussain, and K. Ng ``An Efficient Approach to Searching for Reliable Exceptions'', Pacific Rim International Conference on AI'98 Workshop on Data Mining, Nov. 1998, Singapore
  • Ng, K. and H. Liu ``A Belief-Based Approach to Knowledge Discovery in Databases'', PKAW-98 Pacific Knowledge Acquisition Workshop, Nov. 1998, Singapore
  • Dash, M. and H. Liu ``Similarity Detection among Data Files - A Machine Learning Approach'', IEEE KDEX-97 workshop, Nov. 1997, Newport Beach, California
  • H. Lu, R. Setiono and H. Liu, ``Towards Effective Classification Rule Extraction'', DOOD'95 workshop on Integration of Knowledge Discovery in Databases with Deductive and Object-Oriented Databases, Dec. 1995, Singapore.
  • ``Representation of Designs and Design Knowledge'', (with C.D. Rowles and C. Leckie), IJCAI'91 workshop on ``AI in Design'', August, 1991, Sydney, Australia.
  • ``A Personal News Service Based on a User Model Neural Network'', (with A. Jennings and H. Higuchi), IJCAI'91 workshop on ``Modeling for Intelligent Interaction'', ibid.

Local Conferences

  • ``Making Use of Class Information in Self-Generating Neural Networks'', (with W.X. Wen), Proceedings of ACNN'94 (the 5th Australian Neural Network Conference), Jan. 31 - Feb. 2, 1994, Brisbane, Australia.
  • ``Some Performance Comparisons for SGNT'', (with W.X. Wen and A. Jennings), the 4th Australian National Conference on Artificial Intelligence, November 16-18, 1992, Hobart, Tasmania.
  • ``Critics in Knowledge-Based Design Systems'', (with C. Rowles and W.X. Wen), ibid.
  • ``Artificial Intelligence - Operational Perspective: the CANES Example'', (with C.D. Rowles, C. Leckie, and A. Jennings), National Technology in Government Conference, Feb. 1992, Canberra, Australia.
  • ``Acquisition of Grasping Heuristics for Robot Hand Control'', the 3rd Australian National Conference on Artificial Intelligence, Nov. 1990, Perth, Australia.
  • ``Machine Regeneration of Solver's Problem Solving'' (with H.A. Rowe), the First Annual Conference of Australasian Cognitive Science, Nov. 1990, University of New South Wales, Australia.
  • ``Knowledge-based Multifingered Robot Hand Grasping'', the 3rd Australian National Conference on Robotics, June, 1990, Melbourne, Australia.
  • ``Task analysis: a method of robot hand control'', Simulation'87, Society of Manufacturing Engineers, AI in Manufacturing, October, 1987, Long Beach, California.

Technical Reports and Doctoral Consortia

  • Kaize Ding, Kai Shu, Yichuan Li, Amrita Bhattacharjee, and Huan Liu. ``Challenges in Combating COVID-19 Infodemic - Data, Tools, and Ethics. May 2020. https://arxiv.org/abs/2005.13691
  • Lu Cheng, Yasin N. Silva, Deborah Hall, and Huan Liu. ``Personazlied Learning for Cyberbullying Detection", SBP-BRiMS Doctoral Consortium, 2018. pdf
  • Jundong Li, Kewei Cheng, Suhang Wang, Fred, Morstatter, Rober P. Trevino, Jiliang Tang, and Huan Liu. ``Feature Selection: A Data Perspective", submitted on January 29, 2016. http://arxiv.org/abs/1601.07996
  • Xufei WangHuan Liu, Peng Zhang and Baoxin Li. "Identifying Information Spreaders in Twitter Follower Networks", Technical Report, TR-12-001, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ 85287, 2012.
  • Xia Hu and Huan Liu. "Social Status and Role Analysis of Palin's Email Network", ASUCIDSE-2011-007, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, AZ 85287. Nov. 2011.
  • Pritam Gundecha and Huan Liu. "Minimizing User Vulnerability and Retaining Social Utility in Social Media", ASUCIDSE-2011-006, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, AZ 85287. Nov. 2011.
  • Jiliang Tang and Huna Liu. "Feature Selection with Linked Data in Social Media", ASUCISE-2011-005, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, AZ 85287. Nov. 2011.
  • Huiji Gao, Xufei Wang, Jiliang Tang, and Huan Liu. "Network Denoising in Social Media", TR-11-002, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, AZ 85287, 2011.
  • Pritam Gundecha, Geoffrey Barbier, and Huan Liu."Exploiting Vulnerability to Secure User Privacy on Social Networking Sites", TR-11-001, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, AZ 85287, 2011.
  • Zheng Zhao, Jieping Yefont FACE="CMR12">, Shipeng Yu, and Huan Liu. "Nonlinear Multiple Kernel Learning via Mixture of Probabilistic Kernel Discriminant Analysis", TR-10-008, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ 85287, 2010.
  • Zheng Zhao, Fred Morstatter, Shashvata Sharma, Salem Alelyani, Aneeth Anand, and Huan Liu. "Advancing Feature Selection Research - ASU Feature Selection Repository", TR-10-007, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ 85287, 2010.
  • Lei Tang, Xufei Wang, and Huan Liu. "Community Detection in Multi-Dimensional Networks", TR-10-006, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ 85287, 2010.
  • Lei Tang, Xufei Wang, and Huan Liu. "Understanding Emerging Social Structures - A Group Profiling Approach", Technical Report, TR-10-002, School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ 85287, 2010.
  • Nitin Agarwal, Huan Liu, John Salerno, Shankar Subramanya, and Philip Yu. "Familiar Strangers: Connecting Dots on Blogosphere", Technical Report, TR-08-005, School of Computing Informatics, Arizona State University, Tempe, AZ 85287, 2008.
  • Nitin Agarwal, Magdiel Galan, Huan Liu, Shankar Subramanya. "Clustering with Collective Wisdom - A Comparative Study", Technical Report, TR-08-004, School of Computing Informatics, Arizona State University, Tempe, AZ 85287, 2008.
  • S. Subramanya, B. Li, C. Gries and H. Liu. “Selecting Complementary Features from Multiple Data Sources for Information Integration”, Technical Report, TR-07-009, School of Computing Informatics, Arizona State University, Tempe, AZ 85287, 2007.
  • N. Agarwal, H. Liu, J. Salerno, P. Yu. "Searching for `Familiar Strangers' on Blogosphere: Problems and Challenges", Technical Report, TR-07-008, CSE, School of Computing Informatics, Arizona State University, Tempe, AZ 85287, 2007.
  • N. Agarwal, H. Liu, L. Tang. ``Identifying the Influentials in Blogosphere”, Technical Report, TR-07-004, CSE, School of Computing Informatics, Arizona State University, Tempe, AZ 85287, 2007.
  • Z. Zhao and H. Liu. ``Semi-supervised Feature Selection via Spectral Analysis", Technical Report, TR-06-022, Department of Computer Science and Engineering, Arizona State University, Tempe, AZ 85287, 2006.
  • Y. Ye, L. Yu, and H. Liu.  ``Sparse Linear Discriminant Analysis", Technical Report, TR-06-010, Department of Computer Science and Engineering, Arizona State University, Tempe, AZ 85287, 2006.
  • L. Tang, J. Zhang, and H. Liu, ``Acclimatizing Taxonomic Semantics for Hierarchical Content Classification", Technical Report, TR-06-004, Department fo Computer Scienceand Engineering, Arizona State University, Tempe, AZ 85287, 2006.
  • L. Tang and H. Liu, ``Bia Analysis in Text Classification for Highly Skewed Data", Technical Report, TR-05-008, Department fo Computer Science and Engineering, Arizona State University, Tempe, AZ 85287, 2005.
  • L. Yu, J. Rennert, H. Liu, and M.E. Berens, ``Exploiting Statistical Redundancy in Expression Microarray Data to Foster Biological Relevance", Technical Report, TR-05-005, Department fo Computer Science and Engineering, Arizona State University, Tempe, AZ 85287, 2005.
  • D. Kolippakkam, H. Liu, A. Joy, C. Beaudry, M.E. Berens, ``An Image Mining Approach for Measuring Intensity, Size and Geographical localization of Stained Bodies in Cultured Cells: Application in Apoptosis Detection'', Technical Report, TR-03-010, Department of Computer Science and Engineering, Arizona State University, Tempe, AZ 85287, 2003. pdf.
  • B. Gu, F. Hu, and H. Liu, ``Sampling and Its Applications in Data Mining: A Survey'', School of Computing, National University of Singapore, Technical Report, TRA6-00, 2000. available on-line.
  • F. Hussain, H. Liu, C.L. Tan, and M. Dash, ``Discretization: An Enabling Technique'', Technical Report, TRC6/99, School of Computing, National University of Singapore, June, 1999. available on-line.
  • N.A. Syed, H. Liu and K.K. Sung, ``From Incremental Learning to Model Independent Instance Selection - A Support Vector Machine Approach'', Technical Report, TRA9/99, School of Computing, National University of Singapore, Setp, 1999. available on-line.

Books

Conference Patent Journal Workshop Book

Book Chapters and Encyclopedia Entries

  • Kai Shu,  Ahmadreza Mosallanezhad, and Huan Liu. ``Cross-Domain Fake News Detection on Social Media: A Context-Aware Adversarial Approach", Chapter, in Frontiers in Fake Media Generation and Detection, Springer, pp 215-232, May 2022. DOI: 10.1007/978-981-19-1524-6_9
  • Walaa Alnasser, Ghazaleh Beigi, and Huan Liu. ``An Overview on Protecting User Private-Attribute Information on Social Networks", Handbook of Research on Cyber Crime and Information Privacy, 102-117, 2021
  • Kai Shu, Suhang Wang, Dongwon Lee, and Huan Liu,  ``Mining Disinformation and Fake News: Concepts, Methods, and Recent Advancements", Chapter, in Disinformation, Misinformation, and Fake News in Social Media - Emerging Research Challenges and Opportunities, Lecture Notes in Social Networks, Springer. Editors: Kai Shu, Suhang Wang, Dongwon Lee, and Huan Liu. 2020  pdf
  • Nur Shazwani Kamarudin, Ghazaleh Beigi, Lydia Manikonda, and Huan Liu. ``Social Media for Mental Health: Data, Methods, and Findings", in Open Source Intelligence and Security Informatics, Editors: Mohammad A. Tayebi, Uwe Glaesser, and David Skillicorn. First online August 2020.
  • Kai Shu, H. Russell Bernard, and Huan Liu. ``Studying Fake News via Network Analysis: Detection and Mitigation",  Emerging Resesarch Challenges and Opportunities in Computational Social Network Anaysis and Mining, Editors: Nitin Agarwal, Nima Dokoohaki, and Serpil Tokdemir. Lecture Notes in Social Networks (LNSN), Springer. 2019.  
  • Suhang Wang and Huan Liu. ``Deep Learning for Feature Representation", Chapter 11, Feature Engineering for Machine Learning and Data Analytics, Editors: Guozhu Dong and Huan Liu. Chapman and Hall/CRC Press, 2018.
  • Vineeth Rakesh, Lei Tang, and Huan Liu. ``Feature Learning from Social Graphs", Encyclopedia of Big Data Technologies, edited by Shrif Sakr and Albert Y. Zomaya. Springer Switzerland. First ONline: 13 Feb 2018. DOI: https://doi.org/10.1007/978-3-319-63962-8_273-1
  • Nitin Agarwal and Huan Liu, ``Trust in Blogosphere", In Encyclopedia of Database Systems, August 2, 2017. Editors: Ling Liu and M. Tamer Özsu. doi: 10.1007/978-1-4899-7993-3_438-2.
  • Nitin Agarwal and Huan Liu, ``Time- and Event-Driven Modeling of Blogger Influence", In Encyclopedia of Social Network Analysis and Mining, June 16, 2017. Editors: Reda Alhajj and Jon Rokne. doi:10.1007/978-1-4614-7163-9_378-1, download
  • Liang Wu and Huan Liu, ``Detecting Crowdturfing in Social Media", in Encyclopedia of Social Network Analysis and Mining. June 6, 2017. doi:10.1007/978-1-4614-7163-9_110196-1, download
  • Suhang Wang, Jiliang Tang, and Huan Liu. ''Feature Selection'', Encyclopedia of Machine Learning and Data Mining, Springer. pp503-511. Springer 2017, ISBN 978-1-4899-7685-7a preprint  
  • Liang Wu, Fred Morstatter, Xia Hu, Huan Liu, ``Mining Misinformation in Social Media", in Big Data in Complex and Social Networks. Chapter 5, pages123-152. Edited by My T.Thai, WeiliWu and HuiXiong. Boca Raton, FL CRC Press 2016. pdf
  • Ghazaleh Beigi, Xia Hu, Ross Maciejewski, and Huan Liu. ``An Overview of Sentiment Analysis in Social Media and Its Applications in Disaster Relief", in Sentiment Analysis and Ontology Engineering: An Environment of Computational Intelligence. Springer. Editors: Shyi-Ming Chen and Witold Pedrycz. Studies in Computational Intelligence 639, Springer Switzerland 2016. DOI 10.1007/978-3-319-30319-2. pdf
  • Suhang Wang, Jiliang Tang, and Huan Liu. ``Feature Selection", Encyclopedia of Machine Learning and Data Mining DOI:10.1007/978-1-4899-7502-7_101-1, 2016. pdf
  • Huiji Gao and Huan Liu. ``Time-Aware Personalized Location Recommendation", Encyclopedia of GIS, 2nd Edition, Springer. Editors: Shashi Shekhar and Hui Xiong. pp 1-11. 2016. DOI 10.1007/978-3-319-23519-6_1581-1.
  • Isaac Jones, Lei Tang, and Huan Liu. ``Community Discovery in Muti-Mode Networks", in User Community Discovery. Human-Computer Interaction Series, Springer. Editors: Georgios Paliouras, Symeon Papadopoulos, Dimitrios Vogiatzis, and Yiannis Kompatsiaris. December, 2015. DOI 10.1007/978-3-319-23835-7
  • Shamanth Kumar, Fred Morstatter and Huan Liu. ``Analyzing Twitter data", in Twitter: A Digital Socioscope, Cambridge University Press. Editors: Yelena Mejova, Ingmar Weber, and Michael W. Macy. May, 2015. pdf
  • Xia Hu and Huan Liu. ``Mining and Profiling in Social media", International Encyclopedia of Digital Communication and Society, Blackwell-Wiley in association with the International Communication Association. Editors: Robin Mansell and Peng Hwa Ang. DOI: 10.1002/9781118767771. February 9th, 2015. pdf
  • Mohammad Ali Abbasi, Jiliang Tang, and Huan Liu. ``Trust Aware Recommender Systems", in Machine Learning based Computational Trust, Editors: Xin Liu, Anwitaman Datta, and Ee-Peng Lim. Chapman & Hall/CRC Press. October 29, 2014. pdf
  • Nitin Agarwal, Debanjan Mahata, and Huan Liu. "Time and Event Driven Modeling of Blogger Influence", Encyclopedia of Social Network Analysis and Mining (ESNAM), Springer. Editors: Reda Alhajj and Jon Rokne, 2014. 
  • Jiliang Tang, Salem Alelyani, and Huan Liu. ``Feature Selection for Classification: A Review", in Data Classification: Algorithms and Applications, Editor: Charu Aggarwal. CRC Press, 2014. pdf
  • Zhuo Feng, Pritam Gundecha, and Huan Liu. "Social Provenance", Encyclopedia of Social Network Analysis and Mining (ESNAM), Springer. Editors: Reda Alhajj and Jon Rokne, 2014.
  • Huiji Gao and Huan Liu. ``Data Analysis on Location-Based Social Networks" in Mobile Social Networking: An Innovative Approach, Editors: Alvin Chin and Daqing Zhang, Springer, 2014. pdf
  • Salem Alelyani, Jiliang Tang, and Huan Liu. ``Feature Selection for Clustering: A Review", in Data Clustering: Algorithms and Applications, Editors: Charu Aggarwal and Chandan Reddy. CRC Press, 2013. pdf.
  • Pritam Gundecha and Huan Liu. ``Mining Social Media: A Brief Introduction", Tutorials in Operations Research - New Directions in Informatics, Optimization, Logistics, and Production, pp 1 - 17. Edior: Pitu B. Mirchandani, INFORMS, 2012. slides
  • Xia Hu and Huan Liu. ``Text Analytics in Social Media" in Mining Text Data, Editor: Charu C. Aggawal and Chengxiang Zhai , Springer. pp 385 - 414. March, 2012.
  • Geoffrey Barbier and Huan Liu. "Data Mining in Social Media" in Social Network Data Analytics, Editor: Charu C. Aggawal, Springer, Boston/Dordrecht/London, pp 327 -352. March, 2011.
  • L. Tang and H. Liu. "Understanding Group Structures and Properties in Social Media", in Link Mining: Models, Algorithms and Applications, Editors: Philip Yu, Jiawei Han, and Christos Faloutsos. Springer. pp 163 - 185. 2010.
  • L. Tang and H. Liu. "Graph Mining and Applications to Social Network Analysis", in Managing and Mining Graph Data, Editors: Charu Aggarwal and Haixun Wang. Springer. February, 2010.
  • H. Liu. "Feature Selection: An Overview", in Encyclopedia of Machine Learning, Claude Sammut and Geoffrey I. Webb (Ed.), Springer. September, 2010
  • H. Liu and Z. Zhao. "Manipulating Data and Dimensionality Reduc-tion Methods: Feature Selection", in Encyclopedia of Complexity and Systems Science, Robert Meyers (Ed.), Springer. Part 13, pp 5348 - 5359. Springer. 2009. DOI: 10.1007/978-0-387-30440-3_317.
  • N. Agarwal and H. Liu. "Trust in Blogosphere", in Encyclopedia of Database Systems (EDBS). Part 20, pp. 3187-3191. Editors: Ling Liu and M. Tamer Özsu. SpringerLink. 2009. DOI:10.1007/978-0387-39940-9_348.
  • N. Agarwal, H. Liu, J. Zhang. "A Study of Friendship Networks and Blogosphere", Handbook of Research on Text and Web Mining Technologies, Editors: M. Song and Y. Wu . Information Science Reference (an imprint of IGI Global). pp. 646-669, 2009.
  • P. Refaeilzadeh, L. Tang, and H. Liu. "Cross Validation", in Encyclopedia of Database Systems (EDBS), Editors: Ling Liu and M. Tamer Özsu. Springer, pp6. 2009..
  • N. Agarwal, H. Liu, J.J. Salerno, P.S. Yu. "Searching for `Familiar Strangers' on Blogosphere",Next Generation of Data Mining, Editors: Hillol Kargupta, Jiawei Han, Philip Yu, RajeevMotwani, Vipin Kumar, Chapman & Hall/CRC Press, pp 295 - 315, 2009.
  • M. Dash and H. Liu. "Dimensionality Reduction", in Encyclopedia of Computer Science and Engineering, John Wiley & Sons, Inc. Volume 2, pages 958-966. The ISBN for the 5-Volume set is 978-0-471-38393-2. Benjamin W. Wah, Editor, published in Hoboken, NJ, January 2009. draft pdf
  • Sai Moturu, Lance Parsons, Zheng Zhao, and Huan Liu."Integrative Data Analysis for Biological Discovery", in Encyclopedia of Data Warehousing and Mining, 2nd Edition, Editor: John Wang. Idea Group, Inc. pp 1058 -- 1065, September, 2008.
  • Z. Zhao and H. Liu. "On Interacting Features in Subset Selection", in Encyclopedia of Data Warehousing and Mining, 2nd Edition, Editor: John Wang. Idea Group, Inc. pp 1079 -- 1084, September, 2008.
  • L. Tang, H. Liu, and J. Zhang. "Taxonomy Adaptation for Hierarchical Content Categorization", in Encyclopedia of Data Warehousing and Mining, 2nd Edition, Editor: John Wang. Idea Group, Inc. pp 178 -- 182, September, 2008. 
  • K. Selcuk Candan, Jong Wook Kim, Huan Liu, Reshma Suvarna, and Nitin Agarwal. "Spatial Transformations for Identifying Mappings in Hierarchical Media Data", in Multimedia Data Mining and Knowledge Discovery, Editors: Valery A. Petrushin and Latifur Khan, Springer, 2006.
  • L. Yu and H. Liu. "Data Mining Methods for Microarray Data Analysis", in Encyclopedia of Data Warehousing and Mining, Editor: John Wang, Idea Group Inc. 2005.
  • H. Liu and L. Yu, "Instance Selection", in Encyclopedia of Data Warehousing and Mining, Editor: John Wang, Idea Group Inc. 2005. 2nd Edition, pp 1041 -- 1045, September 2008.
  • H. Liu, A. Mandvikar, and P.G. Foschi, "An Active Learning Approach to Egeria densa Detection in Digital Imagery",  in New Generation of Data Mining Applciations, pdf, IEEE, Feb. 2005.
  • H. Liu, H. Motoda, and L. Yu, "Feature Extraction, Selection, and Construction",  in The Handbook of Data Mining, Lawrence Erlbaum Associates, Inc. Publishers. Editor: N. Ye. PP 409 - 423. 2003.
  • H. Motoda and H. Liu, "Feature Selection",  section contribution to Handbook of Data Mining and Knowledge Discovery, Oxford University Press, New York. Editors: W. Klösgenh and J. Zytkow. PP 208 - 213, 2002.
  • H. Motoda and H. Liu, "Feature Aggregation",  section contribution to Handbook of Data Mining and Knowledge Discovery, Oxford University Press, New York. Editors: W. Klösgenj and . Zytkow. PP 214 - 2172002.
  • H. Liu and H. Motoda, "Data Reduction via Instance Selection",  in Instance Selection and Construction for Data Mining, Editors: H. Liu and H. Motoda, Kluwer Academic Publishers, Boston, USA, February 2001. pp 3--20.
  • B. Gu, F. Hu, and H. Liu, "Sampling: Knowing Whole from Its Part",  in Instance Selection and Construction for Data Mining, Editors: H. Liu and H. Motoda, Kluwer Academic Publishers, Boston, USA, February 2001. pp 21--38.
  • M. Dash and H. Liu, "Unsupervised Feature Ranking and Selection",  in Knowledge Discovery for Business Information Systems. Editors: W. Abramowicz and J. Zurada, Kluwer Academic Publishers, Boston, USA, Dec. 2000. pp 67--88.
  • H. Liu and H. Motoda, "Less Is More",  in Feature Extraction, Construction and Selection: A Data Mining Perspective, Kluwer Academic Publishers. Pages: 3 - 12. Editors: H. Liu and H. Motoda. July 1998.
  • R. Setiono and H. Liu, "Feature Extraction via Neural Networks",  in Feature Extraction, Construction and Selection: A Data Mining Perspective, Kluwer Academic Publishers. Pages: 191 - 204. Editors: H. Liu and H. Motoda. July 1998.
  • H. Liu, "A Family of Efficient Rule Generators", Encyclopedia of Computer Science and Technology, Volume 39, Marcel Dekker, Inc., New York. Pages: 15 - 28. Editors: Allen Kent and James G. Williams. 1998. postscript.

Book Review

  • "Machine Learning, Neural and Statistical Classification" edited by D. Michie, D.J. Spielhalter and C.C. Taylor. SIGART BULLETIN, - A Quarterly Publication of ACM, vol.7 no.1. (January 1996):16.
  • "Neural Networks for Statistical Modeling" by M. Smith. The Australian Computer Journal, vol. 25, no. 4 (November 1993): 165.
  • "AI in Engineering Design" edited by C. Tsong and D. Sriram. The Australian Computer Journal, vol. 25, no. 4 (November 1993): 163.

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