Automatic document clustering of concept hypergraph decompositions

被引：0

作者：

Lin, TY ^{[1
]}

Chiang, IJ ^{[1
]}

机构：

[1] San Jose State Univ, Dept Comp Sci, San Jose, CA 95192 USA

来源：

DATA MINING AND KNOWLEDGE DISCOVERY: THEORY, TOOLS, AND TECHNOLOGY VI | 2004年 / 5433卷

关键词：

document clustering; hypergraph partition; association rules;

D O I：

10.1117/12.543817

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：168 / 177

页数：10

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