Learning multiple graphs for document recommendations
Proceedings of the 17th international conference on World Wide Web
CommTracker: A Core-Based Algorithm of Tracking Community Evolution
ADMA '08 Proceedings of the 4th international conference on Advanced Data Mining and Applications
Mining social network for extracting topic of textual conversations
CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
Simultaneously Finding Fundamental Articles and New Topics Using a Community Tracking Method
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
On Discovering Community Trends in Social Networks
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
A brief survey of computational approaches in social computing
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Mining citation information from CiteSeer data
Scientometrics
Personalized search on Flickr based on searcher's preference prediction
Proceedings of the 20th international conference companion on World wide web
Bibliometric analysis of CiteSeer data for countries
Information Processing and Management: an International Journal
A framework for exploring organizational structure in dynamic social networks
Decision Support Systems
User community discovery from multi-relational networks
Decision Support Systems
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This paper studies the discovery of communities from social network documents produced over time, addressing the discovery of temporal trends in community memberships. We first formulate static community discovery at a single time period as a tripartite graph partitioning problem. Then we propose to discover the temporal communities by threading the statically derived communities in different time periods using a new constrained partitioning algorithm, which partitions graphs based on topology as well as prior information regarding vertex membership. We evaluate the proposed approach on synthetic datasets and a real-world dataset prepared from the CiteSeer.