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KDD
2009
ACM
194views Data Mining» more  KDD 2009»
14 years 8 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 ...
Tianbao Yang, Rong Jin, Yun Chi, Shenghuo Zhu
KDD
2002
ACM
293views Data Mining» more  KDD 2002»
14 years 8 months ago
Automatic Categorization of Web Pages and User Clustering with Mixtures of Hidden Markov Models
We propose mixtures of hidden Markov models for modelling clickstreams of web surfers. Hence, the page categorization is learned from the data without the need for a (possibly cumb...
Alexander Ypma, Tom Heskes
KDD
2005
ACM
149views Data Mining» more  KDD 2005»
14 years 1 months ago
A distributed learning framework for heterogeneous data sources
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
Srujana Merugu, Joydeep Ghosh
KDD
2006
ACM
183views Data Mining» more  KDD 2006»
14 years 8 months ago
Discovering interesting patterns through user's interactive feedback
In this paper, we study the problem of discovering interesting patterns through user's interactive feedback. We assume a set of candidate patterns (i.e., frequent patterns) h...
Dong Xin, Xuehua Shen, Qiaozhu Mei, Jiawei Han
KDD
2007
ACM
124views Data Mining» more  KDD 2007»
14 years 1 months ago
Hierarchical mixture models: a probabilistic analysis
Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...
Mark Sandler