Latent semantic space for web clustering

I-Jen Chiang, Tsau Young Lin, Hsiang Chun Tsai, Jau Min Wong, Xiaohua Hu

研究成果: 書貢獻/報告類型章節

摘要

To organize a huge amount of Web pages into topics, according to their relevance, is the efficient and effective method for information retrieval. Latent Semantic Space (LSS) naturally in the form on some geometric structure in Combinatorial Topology has been proposed for unstructured document clustering. Given a set of Web pages, the set of associations among frequently co-occurring terms in them forms naturally a CONCEPT, which is represented as a set of connected components of the simplicial complexes. Based on these concepts, Web pages can be clustered into meaningful categories.
原文英語
主出版物標題Studies in Computational Intelligence
頁面61-77
頁數17
118
DOIs
出版狀態已發佈 - 2008

出版系列

名字Studies in Computational Intelligence
118
ISSN(列印)1860949X

ASJC Scopus subject areas

  • 人工智慧

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