Generating hypergraph of term associations for automatic document concept clustering

I. J. Chiang, Tsau Young Lin, J. Y J Hsu

研究成果: 書貢獻/報告類型會議貢獻

摘要

This paper presents a novel approach to document clustering using hypergraph decomposition. Given a set of documents, the associations among frequently co-occurring terms in any of the documents define naturally a hypergraph, which can then be decomposed into connected components at various levels. Each connected component represents a primitive concept in the collection. The documents can then be clustered based on the primitive concepts. Experiments with three different data sets from web pages and medical literatures have shown that the proposed unsupervised clustering approach performs significantly better than traditional clustering algorithms, such as k-means, AutoClass and Hierarchical Clustering (HAC). The results indicate that hypergraphs are a perfect model to capture association rules in text and is very useful for automatic document clustering.

原文英語
主出版物標題Proceedings of the Eighth IASTED International Conference on Artificial Intelligence and Soft Computing
編輯A.P. Pobil
頁面181-186
頁數6
出版狀態已發佈 - 2004
事件Proceedings of the Eighth IASTED International Conference on Atificial Intelligence and Soft Computing - Marbella, 西班牙
持續時間: 九月 1 2004九月 3 2004

其他

其他Proceedings of the Eighth IASTED International Conference on Atificial Intelligence and Soft Computing
國家西班牙
城市Marbella
期間9/1/049/3/04

ASJC Scopus subject areas

  • Engineering(all)

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  • 引用此

    Chiang, I. J., Lin, T. Y., & Hsu, J. Y. J. (2004). Generating hypergraph of term associations for automatic document concept clustering. 於 A. P. Pobil (編輯), Proceedings of the Eighth IASTED International Conference on Artificial Intelligence and Soft Computing (頁 181-186)