Difference between revisions of "Class Meeting for 10-802 02/17/2011"

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(Created page with 'This is one of the class meetings on the schedule for the course Social Media Analysis 10-802 in Spring 2011. …')
 
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=== Overview ===
 
=== Overview ===
  
* [http://www.cs.cmu.edu/~wcohen/10-802/02-17-textgraph.pptx Slides]
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* [http://www.cs.cmu.edu/~wcohen/10-802/02-17-prob-graphs.pptx Slides]
  
 
=== Readings ===
 
=== Readings ===
  
* Chang, J., and D. M Blei. 2009. Relational topic models for document networks. In Proc. of Conf. on AI and Statistics (AISTATS’09).
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* [http://128.84.158.114/abs/0912.5410v1 A survey of statistical network models], Goldenberg, Zheng, Fienberg, and Airoldi, Sections 1-3. (If you like, you can glance over Section 4.1 - 4.3, which give this author's view of some of the other models we've discussed.)
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* I will also discuss some of the inference issues for estimating parameters of probabilistic graph models, and will discuss this short paper: Juuso Parkkinen, Adam Gyenge, Janne Sinkkonen and Samuel Kaski. [http://www.cis.hut.fi/projects/mi/papers/mlg09sibm.pdf A block model suitable for sparse graphs.] In MLG 2009, The 7th International Workshop on Mining and Learning with Graphs, Leuven, Belgium, July 2-4,2009.
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=== Optional Readings ===
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I use these two papers as additional background:
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* Snijders, T.A.B. & Nowicki, K., Estimation and prediction for stochastic block models for graphs with latent block structure. Journal of Classification, 14 (1997), 75 - 100.  
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* MS Handcock, AE Raftery, JM Tantrum, Model-based clustering for social networks, Journal of the Royal Stat Soc Series A, 2007, 170(2), pages 301-354

Revision as of 17:13, 5 January 2011

This is one of the class meetings on the schedule for the course Social Media Analysis 10-802 in Spring 2011.

Overview

Readings

  • A survey of statistical network models, Goldenberg, Zheng, Fienberg, and Airoldi, Sections 1-3. (If you like, you can glance over Section 4.1 - 4.3, which give this author's view of some of the other models we've discussed.)
  • I will also discuss some of the inference issues for estimating parameters of probabilistic graph models, and will discuss this short paper: Juuso Parkkinen, Adam Gyenge, Janne Sinkkonen and Samuel Kaski. A block model suitable for sparse graphs. In MLG 2009, The 7th International Workshop on Mining and Learning with Graphs, Leuven, Belgium, July 2-4,2009.

Optional Readings

I use these two papers as additional background:

  • Snijders, T.A.B. & Nowicki, K., Estimation and prediction for stochastic block models for graphs with latent block structure. Journal of Classification, 14 (1997), 75 - 100.
  • MS Handcock, AE Raftery, JM Tantrum, Model-based clustering for social networks, Journal of the Royal Stat Soc Series A, 2007, 170(2), pages 301-354