Mining community structure of named entities from free text

Authors:
Xin Li;Bing Liu
Affiliations:
University of Illinois at Chicago, Chicago, IL;University of Illinois at Chicago, Chicago, IL
Venue:
Proceedings of the 14th ACM international conference on Information and knowledge management
Year:
2005

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Abstract

Although community discovery has been studied extensively in the Web environment, limited research has been done in the case of free text. Co-occurrence of words and entities in sentences and documents usually implies connections among them. In this paper, we investigate the co-occurrences of named entities in text, and mine communities among these entities. We show that identifying communities from free text can be transformed into a graph clustering problem. A hierarchical clustering algorithm is then proposed. Our experiment shows that the algorithm is effective to discover named entity communities from text documents.