Browsing support by highlighting keywords based on user's browsing history

Yutaka Matsuo, Hayajo Fukuta, Mitsuru Ishizuka

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

We develop a browsing support system which learns user's interests and highlights keywords based on a user's browsing history. Monitoring the user's access to the Web enables us to detect "familiar words" for the user. We extract keywords at the current page, which are relevant to the familiar words, and highlight them. The relevancy is measured by the biases of co-occurrence, called IRM (Interest Relevance Measure). Our system consists of three components; a proxy server which monitors access to the Web, a frequency server which stores frequency of words in the accessed Web pages, and a keyword extraction module. We show the effectiveness of our system by experiments.

Original languageEnglish
Pages (from-to)203-211
Number of pages9
JournalTransactions of the Japanese Society for Artificial Intelligence
Volume18
Issue number4
DOIs
Publication statusPublished - 2003
Externally publishedYes

Keywords

  • Browzing support
  • IRM
  • Keyword extraction
  • X test

ASJC Scopus subject areas

  • Artificial Intelligence

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