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» OIDM: Online Interactive Data Mining
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KDD
2009
ACM
379views Data Mining» more  KDD 2009»
13 years 11 months ago
MetaFac: community discovery via relational hypergraph factorization
This paper aims at discovering community structure in rich media social networks, through analysis of time-varying, multi-relational data. Community structure represents the laten...
Yu-Ru Lin, Jimeng Sun, Paul Castro, Ravi B. Konuru...
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
14 years 7 months ago
Probabilistic author-topic models for information discovery
We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
WWW
2009
ACM
14 years 7 months ago
Collaborative filtering for orkut communities: discovery of user latent behavior
Users of social networking services can connect with each other by forming communities for online interaction. Yet as the number of communities hosted by such websites grows over ...
WenYen Chen, Jon-Chyuan Chu, Junyi Luan, Hongjie B...
KDD
2005
ACM
192views Data Mining» more  KDD 2005»
14 years 7 months ago
Modeling and predicting personal information dissemination behavior
In this paper, we propose a new way to automatically model and predict human behavior of receiving and disseminating information by analyzing the contact and content of personal c...
Xiaodan Song, Ching-Yung Lin, Belle L. Tseng, Ming...
WWW
2010
ACM
14 years 2 months ago
Statistical models of music-listening sessions in social media
User experience in social media involves rich interactions with the media content and other participants in the community. In order to support such communities, it is important to...
Elena Zheleva, John Guiver, Eduarda Mendes Rodrigu...