Publications

Additional bibliographic information can be found at DBLP.

Journals and Magazines

Journal Conference Workshop Book

 

  • N. Agarwal and H. Liu. "Blogosphere: Research Issues, Applications, and Tools", SIGKDD Explorations, forthcoming.
  • Z. Zhao and H. Liu. "Searching for Interacting Features in Subset Selection", Intelligent Data Analysis - An International Journal, forthcoming. [45]
  • 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, forthcoming.
  • 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): (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, 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 Engineering, pdf, 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 Explorations,  pdf, 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 [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 Conferences

Journal Conference Workshop Book

  • 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), 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), July 14-18, 2008. Yorktown Heights, NY. pdf (short paper).
  • 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), 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, 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), San Jose, CA, Nov 2-4, 2007. pdf. [90]
  • 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.
  • 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. [85]
  • 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. pdf.
  • Z. Zhao and H. Liu. ``Searching for Interacting Features", The 20th International Joint Conference on AI (IJCAI-07), January 6-12 Hyderabad, India. 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. pdf. [80]
  • 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.
  • 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 [75]
  • 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
  • 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 [70]
  • 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
  • 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. [65] 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
  • 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. [60] 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
  • 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
  • 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. postscript.
  • 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.
  • 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.

International Workshops

Journal Conference Workshop Book

  • 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 Report

  • 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.
  • 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.
  • Nitin Agarwal, Huan Liu, Lei 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.

Journal Conference Workshop Book

Book

  • "Feature Selection for Knowledge Discovery and Data Mining", Huan Liu and Hiroshi Motoda, July 1998, ISBN 0-7923-8198-X, by Kluwer Academic Publishers.
  • “Computational Methods of Feature Selection”, Huan Liu and Hiroshi Motoda, 2008, Chapman and Hall/CRC Press.
  • "Advances in Knowlegde Discovery and Data Mining",  9th Pacific-Asia Conference, PAKDD 2005, Hanoi, Vietnam, May 18-20, 2005, Proceedings. Series: Lecture Notes in Computer Science, Subseries: Lecture Notes in Artificial Intelligence, Vol.  3518. Ho, Tu Bao; Cheung, David; Liu, Huan (Eds.)  ISBN: 3-540-26076-5. Springer.
  • "Instance Selection and Construction for Data Mining", edited, Huan Liu and Hiroshi Motoda, Feburary 2001, ISBN 0-7923-7209-3 by Kluwer Academic Publishers.
  • "Knowledge Discovery and Data Mining - Current Issues and New Applications" - Proceedings of the 4th Pacific-Asia Conference, PAKDD 2000 (Takao Terano, Huan Liu, Arbee L.P. Chen), Kyoto, Japan, April 2000. Springer.
  • ``Feature Extraction, Construction and Selection: A Data Mining Perspective'', (with Hiroshi Motoda), July 1998 (2nd Printing, 2001), ISBN 0-7923-8196-3 by Kluwer Academic Publishers.
  • ``KDD: Techniques and Applications'' - Proceedings of the 1st Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD'97), (Hongjun Lu, Hiroshi Motoda, and Huan Liu), 23-24 Feburary, 1997, Singapore. World Scientific.
  • ``AI'93'', Proceedings of the 6th Australian Joint Conference on Artificial Intelligence, (Chris Rowles, Huan Liu, and Norman Foo), 16-19 November, 1993, Melbourne, Australia. World Scientific.

Book Chapters and Encyclopedia Entries

  • N. Agarwal and H. Liu. "Trust in Blogosphere", in Encyclopedia of Database Systems, forthcoming.
  • P. Refaeilzadeh, L. Tang, and H. Liu. "Cross Validation", in Encyclopedia of Database Systems, forthcoming.
  • Sai Moturu, Lance Parsons, Zheng Zhao, and Huan Liu."Integrative Data Analysis for Biological Discovery", in Encyclopedia of Data Warehousing and Mining, 2nd Edition, Idea Group, Inc. forthcoming.
  • 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.  Forthcoming.
  • H. Liu. "Feature Selection: An Overview", in Encyclopedia of Machine Learning, SClaude Sammut (Ed.), pringer. Forthcoming.
  • Z. Zhao and H. Liu. "On Interacting Features in Subset Selection", in Encyclopedia of Data Warehousing and Mining, 2nd Edition, Idea Group, Inc. Forthcoming.
  • L. Tang, H. Liu, and J. Zhang. "Taxonomy Adaptation for Hierarchical Content Categorization", in Encyclopedia of Data Warehousing and Mining, 2nd Edition, Idea Group, Inc. Forthcoming. 
  • M. Dash and H. Liu. "Dimensionality Reduction", in Encyclopedia of Computer Science and Engineering, John Wiley & Sons, Inc. Forthcoming. draft pdf
  • 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.
  • 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.

Journal Conference Workshop Book
Latest revision: November 20, 2007