Math recitation references:

• Review of probability from a course by David Blei from Princeton U.
• Machine Learning Math Essentials by Jeff Howbert from Washington U.

To read and present:

• S. Brin and L. Page, "The Anatomy of a Large-Scale Hypertextual Web Search Engine," In Proc. 7th International World Wide Web Conference (WWW'98), 1998.
• J. Kleinberg, "Authoritative sources in a hyperlinked environment," In Proc. 9th ACM-SIAM Symposium on Discrete Algorithms, 1998.
• G. Jeh and J. Widom, "Scaling Personalized Web Search," In Proc. of the Twelfth International World Wide Web Conference (WWW'03), 2003.

Other reference:

• Yizhou Sun and Jiawei Han, "Ranking Methods for Networks," accepted by Encyclopedia of Social Network Analysis and Mining, Springer, June 2013.

To read and present:

• X. Xu, N. Yuruk, Z. Feng, and T. Schweiger, "SCAN: a structural clustering algorithm for networks," In Proc. of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD'07), 2007
• M. E. J. Newman, "Detecting community structure in networks," Euro. Phys. J. B 38, 2004.

• J. Shi, J. Malik, "Normalized Cuts and Image Segmentation," IEEE Transactions On Pattern Analysis And Machine Intelligence, vol. 22, no. 8, 2000.

Other references:

• Ulrike Von Luxburg, "A Tutorial on Spectral Clustering," Statistics and Computing, 17:4, 2007.
• Yizhou Sun, Jiawei Han, Peixiang Zhao, Zhijun Yin, Hong Cheng, and Tianyi Wu, "RankClus: Integrating Clustering with Ranking for Heterogeneous Information Network Analysis", Proc. 2009 Int. Conf. on Extending Data Base Technology (EDBT'09), 2009. [pdf]
• Yizhou Sun, Yintao Yu, and Jiawei Han, "Ranking-Based Clustering of Heterogeneous Information Networks with Star Network Schema", Proc. 2009 ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD'09), 2009.[pdf]

To read and present:

• Daniel D. Lee and H. Sebastian Seung, "Algorithms for Non-negative Matrix Factorization," Advances in Neural Information Processing Systems 13 (NIPS'01), 2001.
• C. Ding, T. Li, and W. Peng, "On the equivalence between Non-negative Matrix Factorization and Probabilistic Latent Semantic Indexing," Computational Statistics and Data Analysis 52, 2008.
• E. M. Airoldi, D. M. Blei, S. E. Fienberg, and E. P. Xing, "Mixed Membership Stochastic Blockmodels," Journal of Machine Learning Research 9, 2008.

Other references:

• F. Wang, T. Li, X. Wang, S. Zhu, and C. Ding, "Community discovery using nonnegative matrix factorization," Journal of Data Mining and Knowledge Discovery, 22:3, 2011.
• Brian Karrer, M. E. J. Newman, "Stochastic blockmodels and community structure in networks," Phys. Rev. E 83, 2011.

To read and present:

• Prithviraj Sen, Galileo Namata, Mustafa Bilgic, Lise Getoor, Brian Galligher, and Tina Eliassi-Rad, "Collective Classification in Network Data," AI Magazine 29:3, 2008.
• Xiaojin Zhu and Zoubin Ghahramani, "Learning from Labeled and Unlabeled Data with Label Propagation," CMU-CALD-02-107, 2002.
• J. Leskovec, D. Huttenlocher, and J. Kleinberg, "Predicting postitive and negative links in online social networks," WWW'10, 2010.

Other references:

• F. Wang and C. Zhang, "Label Propagation Through Linear Neighborhoods," ICML'06, 2006.

To read and present:

• D. Metzler and W. B. Croft, "A Markov Random Field Model for Term Dependencies," SIGIR'05, 2005.
• J. Lafferty, A. McCallum, and F. Pereira, "Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data," ICML'01, 2001.
• Frank R. Kschischang, Brendan J. Frey, and Hans-Andrea Loeliger, "Factor Graphs and the Sum-Product Algorithm," IT Trans. Feb. 2001.

Other references:

• Chapter 19 (Undirected graphical models/ Markov random fields), by Kevin Patrick Murphy, from Book: Machine Learning: A Probabilistic Perspective, 2012.
• Charles Sutton and Andrew McCallum, "An introduction to conditional random fields for relational learning," In Getoor, Lise and Taskar, Ben, editors. Introduction to Statistical Relational Learning. MIT Press. 2007.
• Jonathan S. Yedidia, Wiliam T. Freeman, and Yair Weiss, "Constructing Free Energy Approximations and Generalized Belief Propagation Algorithms," IEEE Transactions on Information Theory, 51:7, 2005.

To read and present:

• G. Jen and J. Widom, "SimRank: A measure of structural-context similarity," KDD'02, 2002.
• Peixiang Zhao, Jiawei Han, Yizhou Sun, "P-Rank: A Comprehensive Structural Similarity Measure over Information Networks", Proc. 2009 ACM Conf. on Information and Knowledge Management (CIKM'09), Hong Kong, China, Nov. 2009.
• Yizhou Sun, Jiawei Han, Xifeng Yan, Philip S. Yu, and Tianyi Wu, "PathSim: Meta Path-Based Top-K Similarity Search in Heterogeneous Information Networks", PVLDB 4(11): 992-1003, 2011. (Also, Proc. of 2011 Int. Conf. on Very Large Data Bases (VLDB'11/PVLDB), Seattle, WA, Aug. 2011.)

Other references:

• Cuiping Li, Jiawei Han, Xin Jin, Yizhou Sun, Yintao Yu, and Tianyi Wu, "Fast Computation of SimRank for Static and Dynamic Information Networks", Proc. 2010 Int. Conf. on Extending Data Base Technology (EDBT'10), Lausanne, Switzerland, March 2010.

To read and present:

• D. Gruhl, R. Guha, D. Liben-Nowell, and A. Tomkins, "Information diffusion through blogspace," WWW'04, 2004.
• D. Kempe, J. Kleinberg, and E. Tardos, "Maximizing the Spread of Influence through a Social Network," KDD'03, 2003.
• J. Yang and J. Leskovec, "Modeling Information Diffusion in Implicit Networks," ICDM'10, 2010.

Other references:

• A. Anagnostopou, R. Kumar, and M. Mahdian, "Influence and Correlation in Social Networks," KDD'08, 2008.
• W. Chen, Y. Wang, and S. Yang, "Efficient Influence Maximization in Social Networks," KDD'09, 2009.

To read and present:

• H. Ma, H. Yang, M. Lyu, and I. King, "SoRec: Social Recommendation Using Probabilistic Matrix Factorization," CIKM'08, 2008.
• M. Jamali and M. Ester, "A matrix factorization technique with trust propagation for recommendation in social networks," KDD’10, 2010.
• X.Yu, X. Ren, Y. Sun, Q. Gu, B. Sturt, U. Khandelwal, B. Norick, and J. Han, "Personalized Entity Recommendation: A Heterogeneous Information Network Approach," WSDM'14, 2014.

Other references:

• Y. Koren, R. Bell, and C. Volinsky, "Matrix factorization techniques for recommendation systems," Computer  (Volume:42 ,  Issue: 8 ), 2009.
• C. Wang and D. Blei, "Collaborative topic modeling for recommending scientific articles," KDD'11, 2011.

To read and present:

• D. Liben-Nowell and J. Kleinberg, "The link prediction problem for social networks," CIKM'03, 2003.
• Ben Taskar, Ming-fai Wong, Pieter Abbeel, and Daphne Koller, "Link Prediction in Relational Data," NIPS'03, 2003.
• X. Yu, Q. Gu, M. Zhou, and J. Han, "Citation Prediction in Heterogeneous Bibliographic Networks," SDM'12, 2012.

Other references:

• L. Dietz, S. Bickel, and T. Scheffer, "Unsuperived Prediction of Citation Influences," ICML'07, 2007.
• Yizhou Sun, Rick Barber, Manish Gupta, Charu C. Aggarwal and Jiawei Han, "Co-Author Relationship Prediction in Heterogeneous Bibliographic Networks", Proc. of 2011 Int. Conf. on Advances in Social Network Analysis and Mining (ASONAM'11), Kaohsiung, Taiwan, July 2011.
• Yizhou Sun, Jiawei Han, Charu C. Aggarwal, and Nitesh V. Chawla, "When Will It Happen? --- Relationship Prediction in Heterogeneous Information Networks", Proc. 2012 ACM Int. Conf. on Web Search and Data Mining (WSDM'12), Seattle, WA, Feb. 2012

To read and present:

• X. Yin and W. Tan, "Semi-Supervised Truth Discovery," WWW’11, 2011.
• B. Zhao, B. Rubinstein, J. Gemmell, and J. Han, "A Bayesian approach to discovering truth from conflicting sources for data integration," VLDB’12, 2012.

Other references:

• X. Yin, J. Han, and P. S. Yu, "Truth Discovery with Multiple Conflicting Information Providers on the Web," KDD'07, 2007.

To read and present:

• U Kang, C. E. Tsourakakis, and C. Faloutsos, "PEGASUS: A Peta-Scale Graph Mining System - Implementation and Observations," ICDM'09, 2009.
• A. Kyrola, G. Blelloch, and  C. Guestrin, "GraphChi: Large-Scale Graph Computation on Just a PC," OSDI'12, 2012.

Other references:

• Grzegorz Malewicz, Matthew H. Austern, Aart J. C. Bik, James C. Dehnert, Ilan Horn, Naty Leiser, and Grzegorz Czajkowski, "Pregel: A System for Large-Scale Graph Processing," SIGMOD'10, 2010.