A personalizable agent for semantic taxonomy-based web search

Larry Kerschberg, Wooju Kim, Anthony Scime

Research output: Chapter in Book/Report/Conference proceedingChapter

12 Citations (Scopus)

Abstract

This paper addresses the problem of specifying Web searches and retrieving, filtering, and rating Web pages so as to improve the relevance and quality of hits, based on the user's search intent and preferences. We present a methodology and architecture for an agent-based system, called WebSifter II, that captures the semantics of a user's decision-oriented search intent, transforms the semantic query into target queries for existing search engines, and then ranks the resulting page hits according to a user-specified weighted-rating scheme. Users create personalized search taxonomies via our Weighted Semantic-Taxonomy Tree. Consulting a Web taxonomy agent such as WordNet helps refine the terms in the tree. The concepts represented in the tree are then transformed into a collection of queries processed by existing search engines. Each returned page is rated according to user-specified preferences such as semantic relevance, syntactic relevance, categorical match, page popularity and authority/hub rating.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsWalt Truszkowski, Mike Hinchey, Chris Rouff
PublisherSpringer Verlag
Pages3-31
Number of pages29
ISBN (Print)9783540451730
DOIs
Publication statusPublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2564
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kerschberg, L., Kim, W., & Scime, A. (2003). A personalizable agent for semantic taxonomy-based web search. In W. Truszkowski, M. Hinchey, & C. Rouff (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 3-31). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2564). Springer Verlag. https://doi.org/10.1007/978-3-540-45173-0_1