research
My research interests include problems relating to dynamic multi-relational social network analysis – in particular, community dynamics, social information summarization and representation. My current research, Community Discovery in Dynamic, Rich Media Social Networks, focuses on extracting human communities that collaborate around certain topics or media sharing activities.
I have also conducted work on spam blog ("splog") detection based on link connectivity and temporal properties of blogs. There I combined traditional content based features with temporal and link signatures with excellent results.
Prior to my Ph.D. study, I was interested in the area of computer graphics, with a particular concentration on non-photorealistic rendering. In my master thesis, I proposed a rendering framework that renders three-dimensional models in a synthetic Chinese painting style.
Social Network Analysis - Community Discovery in Dynamic, Rich Media Social Networks
With the rapid proliferation of different types of social media, such as instant messaging (e.g., AIM, MSN, Skype), media sharing sites (e.g., Flickr, YouTube), blogs (e.g., Blogger, WordPress, LiveJournal), wikis (e.g., Wikipedia, PBWiki), microblogs (e.g., Twitter, Jaiku), social networks (e.g., MySpace, Facebook), to mention a few, users routinely produce (e.g. blogs) and consume media (e.g. YouTube) as well as interact with each other through a wide array of functionality provided by various social media. These social media depend largely on implicit communities of online users to deliver value. Identifying and analyzing the dynamics of such latent communities can lead to improved functionality of the social media as well as provide insight into the design of future online collaborative services. The problem is particularly important in the enterprise domain where extracting emergent community structure on enterprise social media, can help in forming new collaborative teams, in expertise discovery, and guide long term enterprise reorganization.
My work studies three aspects of community analysis in dynamic, rich media social networks: (1) Community evolution – How do we identify communities in large scale, dynamic social networks, and analyze their structures and evolutions? (2) Community summarization – How do we summarize community activities, in order to trace community interests or retrieve community generated content? (3) Multi-relational communities – How do we discover communities when the social networks exist in a highly connected web of contexts (e.g., social groups, geographic locations, time, etc.)?
Community evolution
- Yu-Ru Lin, Yun Chi, Shenghuo Zhu, Hari Sundaram and Belle Tseng (2009) "Analyzing Communities and Their Evolutions in Dynamics Networks", to appear in ACM Trans. on Knowledge Discovery from Data, special issue on Social Computing, Behavioral Modeling, and Prediction (TKDD) [abstract]
- Yu-Ru Lin, Yun Chi, Shenghuo Zhu, Hari Sundaram and Belle Tseng (2008) "FaceNet: A Framework for Analyzing Communities and Their Evolutions in Dynamics Networks", in Proceedings of the 17th International World Wide Web Conference (WWW 2008) [abstract][slides][pdf]
- Yu-Ru Lin, Hari Sundaram, Yun Chi, Jun Tatemura and Belle Tseng (2007) "Blog Community Discovery and Evolution Based on Mutual Awareness Expansion", in Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, Pages 48-56 (WI 2007) [pdf][abstract][slides]
Community summarization
- Yu-Ru Lin, Hari Sundaram and Aisling Kelliher (2009) "JAM: Joint Action Matrix Factorization for Summarizing a Temporal Heterogeneous Social Network", to appear in Proceedings of International AAAI Conference on Weblogs and Social Media (ICWSM 2009) [abstract]
- Yu-Ru Lin, Hari Sundaram and Aisling Kelliher (2009) "Summarization of Large Scale Social Network Activity", in Proceedings of 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2009) [abstract]
- Yu-Ru Lin, Hari Sundaram and Aisling Kelliher (2008) "Summarization of Social Activity over Time: People, Actions and Concepts in Dynamic Networks" (poster), in Proceedings of ACM 17th Conference on Information and Knowledge Management (CIKM 2008) [abstract]
Multi-relational communities
- Yu-Ru Lin, Jimeng Sun, Paul Castro, Ravi Konuru, Hari Sundaram and Aisling Kelliher (2009) "MetaFac: Commmunity Discovery via Relational Hypergraph Factorization", to appear in Proceedings of the 15th ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD 2009) [abstract]
- Yu-Ru Lin, Jimeng Sun, Paul Castro, Ravi Konuru, Hari Sundaram and Aisling Kelliher (2009) "Extracting Community Structure through Relational Hypergraphs" (poster), in Proceedings of the 18th International World Wide Web Conference (WWW 2009) [abstract][pdf]
Social media and human interactions
- Yu-Ru Lin, Hari Sundaram, Munmun De Choudhury and Aisling Kelliher (2009) "Temporal Patterns in Social Media Streams: Theme Discovery and Evolution Using Joint Analysis of Content and Context", to appear in Proceedings of 2009 IEEE International Conference on Multimedia and Expo (ICME 2009) [abstract]
- Munmun De Choudhury, Hari Sundaram, Yu-Ru Lin, Ajita John and Doree Duncan Seligmann (2009) "Connecting Content to Community in Social Media via Image Content, User Tags and User Communication", to appear in Proceedings of 2009 IEEE International Conference on Multimedia and Expo (ICME 2009) [abstract]
- Yu-Ru Lin, Hari Sundaram and Aisling Kelliher (2008) "Community Trajectory: Discovery of Evolutionary Collaboration Patterns Based on Event Co-participation" [link]
- Yu-Ru Lin and Hari Sundaram (2007) "Blog Antenna: Summarization of Personal Blog Temporal Dynamics Based on Self-similarity Factorization", in Proceedings of IEEE International Conference on Multimedia and Expo (ICME2007) [pdf][abstract]
- Joshua Watts and Yu-Ru Lin (2006) "Agent-based Model of a Simple Prehistoric Exchange System", Archaeological Sciences of the Americas 2006. [pdf][code]
- Yu-Ru Lin, Hari Sundaram, Yun Chi, Jun Tatemura and Belle Tseng (2006) "Discovery of Blog Communities based on Mutual Awareness", in Proceedings of the 3rd Annual Workshop on Weblogging Ecosystem: Aggregation, Analysis and Dynamics, 15th World Wid Web Conference [pdf][abstract]
Adversarial Information Retrieval on the Web – Splog Detection
Our work deals with detecting spam blogs (splogs), a major problem in the blogosphere. Splogs are undesirable blogs meant to attract search engine traffic, used solely for promoting affiliate sites.
- Yu-Ru Lin, Hari Sundaram, Yun Chi, Jun Tatemura and Belle Tseng (2008) "Detecting Splogs via Temporal Dynamics using Self-similarity Analysis", in ACM Transactions on the Web (TWEB) Volume 2, Issue 1 (February 2008) [pdf][abstract]
- Yu-Ru Lin, Hari Sundaram, Yun Chi, Jun Tatemura and Belle Tseng (2007) "Splog Detection Using Self-similarity Analysis on Blog Temporal Dynamics", in Proceedings of the 3rd International Workshop on Adversarial Information Retrieval on the Web (AIRWeb 2007) [pdf][abstract]
- Yu-Ru Lin, Hari Sundaram, Yun Chi, Jun Tatemura and Belle Tseng (2007) "Splog Detection Using Content, Time and Link Structure", in Proceedings of IEEE International Conference on Multimedia and Expo (ICME 2007) [pdf][abstract]
- Yu-Ru Lin, Wen-Yen Chen, Xiaolin Shi, Richard Sia, Xiaodan Song, Yun Chi, Koji Hino, Hari Sundaram, Jun Tatemuran and Belle Tseng (2006) "The splog detection task and a solution based on temporal and link properties", in The Fifteeth Text REtrieval Conference Proceedings (TREC 2006) [pdf][abstract]
Computer Graphics – Non-photorealistic Rendering
The research considers non-photorealistic rendering (NPR) technique that deals with problem of reducing the visual complexity while maintaining the aesthetic value of synthesized images. NPR stems from a key insight: artistic works are not necessarily photorealistic, whereas the observer can still comprehend the information delivered by the artists, based on the artistic context of the work. Theses papers present a framework for automatically drawing three-dimensional trees (one of the essential painting subjects in Chinese landscape painting) in Chinese ink painting style. We address the problem by leveraging computer rendering techniques with knowledge about Chinese painting. Our approach includes image-based outline rendering and texture generation according to the information captured from the three-dimensional objects. We introduce novel reference maps to analyze the information for creating the brush strokes, textures, and inking parameters of washing tone. Stylized textures are created by procedurally defining the texture patterns. The analytical painting framework can be extended to draw other subjects in Chinese ink painting style. We demonstrate the results of our method with excellent 2D/3D rendering results. (details and papers)