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KDD
2009
ACM
164views Data Mining» more  KDD 2009»
16 years 4 months ago
Social influence analysis in large-scale networks
In large social networks, nodes (users, entities) are influenced by others for various reasons. For example, the colleagues have strong influence on one's work, while the fri...
Jie Tang, Jimeng Sun, Chi Wang, Zi Yang
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
16 years 4 months ago
Efficient methods for topic model inference on streaming document collections
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
Limin Yao, David M. Mimno, Andrew McCallum
KDD
2009
ACM
206views Data Mining» more  KDD 2009»
16 years 4 months ago
Ranking-based clustering of heterogeneous information networks with star network schema
A heterogeneous information network is an information network composed of multiple types of objects. Clustering on such a network may lead to better understanding of both hidden s...
Yizhou Sun, Yintao Yu, Jiawei Han
KDD
2008
ACM
284views Data Mining» more  KDD 2008»
16 years 4 months ago
Community evolution in dynamic multi-mode networks
A multi-mode network typically consists of multiple heterogeneous social actors among which various types of interactions could occur. Identifying communities in a multi-mode netw...
Lei Tang, Huan Liu, Jianping Zhang, Zohreh Nazeri
KDD
2008
ACM
165views Data Mining» more  KDD 2008»
16 years 4 months ago
Colibri: fast mining of large static and dynamic graphs
Low-rank approximations of the adjacency matrix of a graph are essential in finding patterns (such as communities) and detecting anomalies. Additionally, it is desirable to track ...
Hanghang Tong, Spiros Papadimitriou, Jimeng Sun, P...
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