Automatic document clustering of concept hypergraph decompositions

Tsau Young Lin, I-Jen Chiang

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

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsB.V. Dasarathy
Pages168-177
Number of pages10
Volume5433
DOIs
Publication statusPublished - 2004
EventData Mining and Knowledge Discovery: Theory, Tools, and Technology VI - Orlando, FL, United States
Duration: Apr 12 2004Apr 13 2004

Other

OtherData Mining and Knowledge Discovery: Theory, Tools, and Technology VI
CountryUnited States
CityOrlando, FL
Period4/12/044/13/04

Keywords

  • Association rules
  • Document clustering
  • Hypergraph partition

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

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  • Cite this

    Lin, T. Y., & Chiang, I-J. (2004). Automatic document clustering of concept hypergraph decompositions. In B. V. Dasarathy (Ed.), Proceedings of SPIE - The International Society for Optical Engineering (Vol. 5433, pp. 168-177) https://doi.org/10.1117/12.543817