Wise search engine based on LSI

Yang Jianxiong, Junzo Watada

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

Abstract

The objective of this work is to provide, as a search engine, latent semantic indexing (LSI), which is a classical method to produce optimal approximations of a term-document matrix and has been used for textual information mining. The use of this technique is examining mine content which based web document, using keyword features of documents. Experimental results show that together with both textual and latent features LSI can extract the underlying semantic structure of web documents, thus improve the search engine performance significantly.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages126-136
Number of pages11
Volume5980 LNAI
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event6th International Workshop on Agents and Data Mining Interaction, ADMI 2010 - Toronto, ON
Duration: 2010 May 112010 May 11

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5980 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other6th International Workshop on Agents and Data Mining Interaction, ADMI 2010
CityToronto, ON
Period10/5/1110/5/11

Keywords

  • data mining
  • Latent semantic indexing
  • search engine
  • semantic web

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Jianxiong, Y., & Watada, J. (2010). Wise search engine based on LSI. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5980 LNAI, pp. 126-136). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5980 LNAI). https://doi.org/10.1007/978-3-642-15420-1_11