PaCK: Scalable parameter-free clustering on K-partite graphs

Jingrui He, Hanghang Tong, Spiros Papadimitriou, Tina Eliassi-Rad, Christos Faloutsos, Jaime Carbonell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Given an author-paper-conference graph, how can we automatically find groups for author, paper and conference respectively. Existing work either (1) requires fine tuning of several parameters, or (2) can only be applied to bipartite graphs (e.g., author-paper graph, or paper-conference graph). To address this problem, in this paper, we propose PaCK for clustering such k-partite graphs. By optimizing an information-theoretic criterion, PaCK searches for the best number of clusters for each type of object and generates the corresponding clustering. The unique feature of PaCK over existing methods for clustering k-partite graphs lies in its parameter-free nature. Furthermore, it can be easily generalized to the cases where certain connectivity relations are expressed as tensors, e.g., time-evolving data. The proposed algorithm is scalable in the sense that it is linear with respect to the total number of edges in the graphs. We present the theoretical analysis as well as the experimental evaluations to demonstrate both its effectiveness and efficiency.

Original languageEnglish (US)
Title of host publicationSociety for Industrial and Applied Mathematics - 9th SIAM International Conference on Data Mining 2009, Proceedings in Applied Mathematics
Pages1278-1287
Number of pages10
Volume3
Publication statusPublished - 2009
Externally publishedYes
Event9th SIAM International Conference on Data Mining 2009, SDM 2009 - Sparks, NV, United States
Duration: Apr 30 2009May 2 2009

Other

Other9th SIAM International Conference on Data Mining 2009, SDM 2009
CountryUnited States
CitySparks, NV
Period4/30/095/2/09

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ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Software
  • Applied Mathematics

Cite this

He, J., Tong, H., Papadimitriou, S., Eliassi-Rad, T., Faloutsos, C., & Carbonell, J. (2009). PaCK: Scalable parameter-free clustering on K-partite graphs. In Society for Industrial and Applied Mathematics - 9th SIAM International Conference on Data Mining 2009, Proceedings in Applied Mathematics (Vol. 3, pp. 1278-1287)