C&C: an effective algorithm for extracting web community cores

Authors:
Xianchao Zhang;Yueting Li;Wenxin Liang
Affiliations:
School of Software, Dalian University of Technology, China;School of Software, Dalian University of Technology, China;School of Software, Dalian University of Technology, China
Venue:
DASFAA'10 Proceedings of the 15th international conference on Database systems for advanced applications
Year:
2010

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Abstract

Communities is a significant pattern of the Web. A community is a group of pages related to a common topic. Web communities are able to be characterized by dense bipartite subgraphs. Each community almost surely contains at least one core. A core is a complete bipartite graph (CBG). Focusing on the issues of extracting such community cores from the Web, in this paper we propose an effective C&C algorithm based on combination and consolidation to extract all embedded cores in web graphs. Experiments on real and large data collections demonstrate that the proposed algorithm C&C is efficient and effective for the community core extraction because: 1) all the largest emerging cores can be identified; 2) identifying all the embedded cores with different sizes only requires one-pass execution of C&C; 3) the extraction process needs no user-determined parameters in C&C.