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
收藏
页码：168 / 177
页数：10
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