Sciweavers

Share
KDD
2009
ACM

Combining link and content for community detection: a discriminative approach

9 years 7 months ago
Combining link and content for community detection: a discriminative approach
In this paper, we consider the problem of combining link and content analysis for community detection from networked data, such as paper citation networks and Word Wide Web. Most existing approaches combine link and content information by a generative model that generates both links and contents via a shared set of community memberships. These generative models have some shortcomings in that they failed to consider additional factors that could affect the community memberships and isolate the contents that are irrelevant to community memberships. To explicitly address these shortcomings, we propose a discriminative model for combining the link and content analysis for community detection. First, we propose a conditional model for link analysis and in the model, we introduce hidden variables to explicitly model the popularity of nodes. Second, to alleviate the impact of irrelevant content attributes, we develop a discriminative model for content analysis. These two models are unified s...
Tianbao Yang, Rong Jin, Yun Chi, Shenghuo Zhu
Added 25 Nov 2009
Updated 25 Nov 2009
Type Conference
Year 2009
Where KDD
Authors Tianbao Yang, Rong Jin, Yun Chi, Shenghuo Zhu
Comments (0)
books