Topic-based Intelligent Support System for Information Retrieval

Yasufumi Takama, Kaoru Hirota

Research output: Contribution to journalArticlepeer-review

Abstract

We propose a new concept of intelligent support systems for topic-based information retrieval. As information retrieval (IR) on the World Wide Web (WWW) becomes widespread, new types of tools and systems that do not only find specific pages the user wants, but also and helping the user learn about a particular field of interest are increasingly needed. Two systems based on this consideration are introduced in this paper. One is the Fish View system for supporting document-ordering. It focuses on the user's document-ordering (making diagrams) while reading, and the user's viewpoint is represented by a combination of a small number of concepts taken from the existing concept structure dictionary. The extracted viewpoint can be used for measuring the similarity among documents, using fish eye matching, the extended Vector Space Model. The other is the query network for visualization of the topic distribution through WWW IR, and its concept employing the Immune Network model is introduced with preliminary experiments.

Original languageEnglish
Pages (from-to)457-463
Number of pages7
JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
Volume4
Issue number6
DOIs
Publication statusPublished - Nov 2000
Externally publishedYes

Keywords

  • Immune network
  • Information retrieval
  • Information visualization
  • WWW

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