Automatic document clustering of concept hypergraph decompositions

Tsau Young Lin, I-Jen Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsB.V. Dasarathy
Number of pages10
Publication statusPublished - 2004
EventData Mining and Knowledge Discovery: Theory, Tools, and Technology VI - Orlando, FL, United States
Duration: Apr 12 2004Apr 13 2004


OtherData Mining and Knowledge Discovery: Theory, Tools, and Technology VI
Country/TerritoryUnited States
CityOrlando, FL


  • Association rules
  • Document clustering
  • Hypergraph partition

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics


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