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Mining Community Structure of Named Entities from Free Text (2005)
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| Venue: | in Conference on Information and Knowledge Management |
| Citations: | 8 - 0 self |
BibTeX
@INPROCEEDINGS{Li05miningcommunity,
author = {Xin Li and Bing Liu},
title = {Mining Community Structure of Named Entities from Free Text},
booktitle = {in Conference on Information and Knowledge Management},
year = {2005}
}
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Abstract
Although community discovery based on social network has been studied extensively in the Web hyperlink environment, limited research has been done in the case of Web documents. The co-occurrence of Words and entities in sentences and documents usually implies some connections among them. Studying such connections may reveal important relationships. In this paper, we investigate the cooccurrences of named entities in Web pages and blogs, and mine communities among those entities. We show that identifying communities in such an environment can be transformed into a graph clustering problem. A hierarchical clustering algorithm is then proposed, which exploits triangle structures within the graph and the mutual information between vertices. Our empirical study shows that the proposed algorithm is promising in discovering communities from Web documents.
