Automatic document clustering of concept hypergraph decompositions

Tsau Young Lin; I-Jen Chiang

doi:10.1117/12.543817

Automatic document clustering of concept hypergraph decompositions

Tsau Young Lin, I-Jen Chiang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 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 language	English
Title of host publication	Proceedings of SPIE - The International Society for Optical Engineering
Editors	B.V. Dasarathy
Pages	168-177
Number of pages	10
Volume	5433
DOIs	https://doi.org/10.1117/12.543817
Publication status	Published - 2004
Event	Data Mining and Knowledge Discovery: Theory, Tools, and Technology VI - Orlando, FL, United States Duration: Apr 12 2004 → Apr 13 2004

Other

Other	Data Mining and Knowledge Discovery: Theory, Tools, and Technology VI
Country/Territory	United States
City	Orlando, FL
Period	4/12/04 → 4/13/04

Keywords

Association rules
Document clustering
Hypergraph partition

ASJC Scopus subject areas

Electrical and Electronic Engineering
Condensed Matter Physics

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10.1117/12.543817

Cite this

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title = "Automatic document clustering of concept hypergraph decompositions",

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.",

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author = "Lin, {Tsau Young} and I-Jen Chiang",

year = "2004",

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AU - Chiang, I-Jen

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AB - 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.

KW - Association rules

KW - Document clustering

KW - Hypergraph partition

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DO - 10.1117/12.543817

M3 - Conference contribution

AN - SCOPUS:3543147684

VL - 5433

SP - 168

EP - 177

BT - Proceedings of SPIE - The International Society for Optical Engineering

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T2 - Data Mining and Knowledge Discovery: Theory, Tools, and Technology VI

Y2 - 12 April 2004 through 13 April 2004

ER -

Automatic document clustering of concept hypergraph decompositions

Abstract

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Keywords

ASJC Scopus subject areas

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