Course description: This course surveys recent development in data mining and machine learning in the areas of social networks and social media, and transfer learning. Posts can be found on the Twitter site, and course specific items are posted on the course newsgroup Course Newsgroup.
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Week Lecture Reading1
Social Networks and Graphs: Basic Concepts (PPT)
Feb 9 class: Comp 621U students are encouraged to attend the tutorials at ACM WSDM 2011 Conference, in Hong Kong, on Feb 9, 2011.
- Chapters 1: Overview and 2: Graphs from Kleinberg&Easley's Book: Networks, Crowds and Markets.
- http://dmml.asu.edu/cdm/
- Planetary-Scale Views on a Large Instant-Messaging Network, WWW 2008 (PPT)
- An Experimental Study of the Small World Problem
- Zachary's Karate Club, Journal of Anthropological Research (Karate?)
- J. Kleinberg. The small-world phenomenon: An algorithmic perspective. Proc. 32nd ACM Symposium on Theory of Computing, 2000.
2 Community Detection and Graph-based Clustering
- http://dmml.asu.edu/cdm/ (Chapter 3)
- Slides
- Santo Fortunato, Community detection in graphs. Physics Reports, 486(3:75 – 174)
- Lei Tang and Huan Liu, Community Detection in Multi-Dimensional Networks (Chapter 3)
- U. Luxburg, A Tutorial on Spectral Clustering
- Learning and Predicting the Evolution of Social Networks, IEEE Intelligent Systems, Special Issue on Social Learning 2010 (slides)
- J. Leskovec, et al. Empirical Comparison of Algorithms for Network Community Detection, WWW 2010. (slides)
- 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 (slides)
3 Information Influence, Diffusion and Outbreak Detection (Slides) (Note: classroom changed to 2465 (Lift 25/26) after Feb 21,2011)
- Chapters 16, 18 and 19 of Book by David Easley and Jon Kleinberg
- D. Gruhl, R. Guha, D. Liben-Nowell, A. Tomkins. Information Diffusion through Blogspace. In Proc. International WWW Conference, 2004.
- W. Che, C. Wang, Y. Wang. Scalable influence maximization for prevalent viral marketing in large-scale social networks In Proc. of KDD 2010
On Thursday, we will be discussing the following papers:
- J. Leskovec, A. Krause, C. Guestrin, C. Faloutsos, J. VanBriesen, N. Glance. Cost-effective Outbreak Detection in Networks. In Proc. KDD 2007 (Slides)
- M. Rodriguez, J. Leskovec, A. Krause, Inferring Networks of Diffusion and Influence. In Proc. KDD 2010 (Slides)
- Mislove et al. You are Who You Know WSDM 2010 (Slides)
- C. Tan, J. Tang, J. Sun, Q. Lin, F. Wang. Social action tracking via noise tolerant time-varying factor graphs. In Proc. of KDD 2010 (Slides)
- Pal and Counts, Identifying Topical Authorities in Microblogs, WSDM 2011 (PPT) ( also read the TwitterRank Paper, Slides)
4 Link Prediction and Collaborative Filtering (Slides)
- Ryan N. Lichtenwalter, Jake T. Lussier, Nitesh V. Chawla, New Perspectives and Methods in Link Prediction, KDD 2010
- Chapters 14 of Network Book by David Easley and Jon Kleinberg
- David Liben-Nowell and Jon Kleinberg, The link-prediction problem for social networks, Journal of the American Society for Information Science and Technology, Volume 58 Issue 7, May 2007
- Elena Zheleva, Lise Getoor, Jennifer Golbeck, Ugur Kuter, Using Friendship Ties and Family Circles for Link Prediction, SNAKDD Workshop, 2008.
- Yehuda Koren, Collaborative Filtering with Temporal Dynamics. KDD 2009.
- Davison et al. The YouTube Video Recommendation System. RecSys 2010.
- Other References
5 Social Tagging and Learning
- ECML PKDD 2009 Challenge: Introduction, Remarks
- Börkur Sigurbjörnsson and Roelof van Zwol, Flickr Tag Recommendation based on Collective Knowledge, WWW 2008 (Slides)
- Meiqun Hu, Ee-Peng Lim and Jing Jiang, A Probabilistic Approach to Personalized Tag Recommendation. SocialCom'10. (Slides)
- Steffen Rendle and Lars Schmidt-Thieme, Pairwise Interaction Tensor Factorization for Personalized Tag Recommendation, WSDM 2010 (Slides)
- Dawei Yin Zhenzhen Xue Liangjie Hong Brian D. Davison, A Probabilistic Model for Personalized Tag Prediction. KDD 2010 (Slides)
Other Readings
- Ralf Krestel, Peter Fankhauser, and Wolfgang Nejdl. Latent Dirichlet Allocation for Tag Recommendation. RecSys'09.
- Caimei Lu, Tony Hu et al. The topic-perspective model for social tagging systems. KDD 2010
- Yang Song et al. Real-time Automatic Tag Recommendation. SIGIR 2008.
- Lei Wu et al., Learning to Tag, WWW 2009 (Slides)
- Lei Wu et al. Flickr Distance. ACM Multimedia 2008 (Slides)
6
- Collective intelligence and Crowd-sourcing
- Transfer Learning in Social Network Applications
- Introduction: WSDM Tutorial on Crowdsourcing (the Turk on Youtube) (Slides)
- Twitter Earthquake Detector , ESP Game
- Takeshi Sakaki, Makoto Okazaki, Yutaka Matsuo: Earthquake shakes Twitter users: real-time event detection by social sensors. WWW 2010, 851-860. (Slides)
- Get Another Label? Improving Data Quality and Data Mining Using Multiple, Noisy Labelers Sheng, S., F. Provost and P.Ipeirotis. ACM KDD 2009. (Slides)
- Daniel E. Rose, A9.com Inc. Crowdsourcing for Relevance Evaluation, CIKM 2008
- Quality Management on Amazon Mechanical Turk, P. Ipeirotis, F. Provost, and J. Wang. Proceedings of the Second Human Computation Workshop (KDD-HCOMP 2010).
- http://txteagle.com/ , Txteagle Talk
- The rise of crowdsourcing, J Howe - Wired magazine, 2006
- Transfer Learning Survey, (Transfer Learning and CF)
7-13 Student Presentations (March 22--May 12)
May 17 Final Project Due
- Student Projects
- An Introduction to KDDCUP and Twitter Data, presented by Nathan Liu (also see the project data page for a subset of the problems: http://www.cse.ust.hk/~nliu/comp621-kddcup.html, and a discussion session is planned in Room 3401, on 07 Apr 2011 (Thu) at 16:30-17:30)
- An Introduction to a new Competition on Match-making, presented by Weike Pan
Data Sets
Conferences
Other References