Latent semantic space for web clustering

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

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

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.

Original languageEnglish
Title of host publicationStudies in Computational Intelligence
Pages61-77
Number of pages17
Volume118
DOIs
Publication statusPublished - 2008

Publication series

NameStudies in Computational Intelligence
Volume118
ISSN (Print)1860949X

ASJC Scopus subject areas

  • Artificial Intelligence

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