Topic structure mining using temporal co-occurrence

Authors:
Hiroyuki Toda;Hiroyuki Kitagawa;Ko Fujimura;Ryoji Kataoka
Affiliations:
NTT Corporation, Kanagawa, Japan;University of Tsukuba, Tsukuba-shi, Ibaraki, Japan;NTT Corporation, Kanagawa, Japan;NTT Corporation, Kanagawa, Japan
Venue:
Proceedings of the 2nd international conference on Ubiquitous information management and communication
Year:
2008

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Abstract

This paper proposes a topic structure mining method for document sets that include time stamps. Topic structure mining is a text mining method that uses the graph structure that represents the document pair similarities in the document set. This method yields not only topic extraction from documents and clustering of documents but also extracts the relationship between clusters and the meaning of each document in the cluster. Our method combines temporal co-occurrence with document similarity in constructing the graph structure. We also report evaluation results and the effectiveness of the proposed method.