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Proceedings Paper

Automatic document clustering of concept hypergraph decompositions
Author(s): Tsau Young Lin; I-Jen Chiang
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Paper Abstract

This paper presents an approach to classify/cluster the web documents by decompositions of hypergraphs. The various levels of co-occurring frequent terms, called association rules (undirected rules), of documents form a hypergraph. Clustering methods is then applied to analyze such hypergraphs; a simple and fast clustering algorithm is used to decomposing hypergraph into connected components. Each connected component represents a primitive concept within the given documents. The documents will then be classified/clustered by such primitive concepts.

Paper Details

Date Published: 12 April 2004
PDF: 10 pages
Proc. SPIE 5433, Data Mining and Knowledge Discovery: Theory, Tools, and Technology VI, (12 April 2004); doi: 10.1117/12.543817
Show Author Affiliations
Tsau Young Lin, San Jose State Univ. (United States)
I-Jen Chiang, Taipei Medical University (Taiwan)

Published in SPIE Proceedings Vol. 5433:
Data Mining and Knowledge Discovery: Theory, Tools, and Technology VI
Belur V. Dasarathy, Editor(s)

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