Personal keyword extraction from the Web

Junichiro Mori, Yutaka Matsuo, Mitsuru Ishizuka

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

With the currently growing interest in the Semantic Web, personal metadata to model a user and the relationship between users is coming to play an important role in the Web. This paper proposes a novel keyword extraction method to extract personal information from the Web. The proposed method uses the Web as a large corpus to obtain co-occurrence information of words. Using the co-occurrence information, our method extracts relevant keywords depending on the context of a person. Our evaluation shows better performance to other keyword extraction methods. We give a discussion about our method in terms of general keyword extraction for the Web.

Original languageEnglish
Pages (from-to)337-345
Number of pages9
JournalTransactions of the Japanese Society for Artificial Intelligence
Volume20
Issue number5
Publication statusPublished - 2005
Externally publishedYes

Keywords

  • Keyword extraction
  • Metadata
  • Search engine
  • Social network
  • Word co-occurrence

ASJC Scopus subject areas

  • Artificial Intelligence

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