Detecting innovative topics based on user-interest ontology

Makoto Nakatsuji*, Makoto Yoshida, Toru Ishida

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)

Abstract

In this paper, we detect "innovative topics", those that are new and hopefully interesting to the user. We try to expand user interests significantly by letting the user browse those topics. We first generate user-interest ontologies that allow user profiles to be constructed as a hierarchy of classes where a user interest weight is assigned to each class and instance. Next, we measure the similarity between user interests by using interest weights on their user-interest ontologies and generate user group GU that has high similarity to user u. The innovative topics for u are then detected by determining a suitable size of GU and analyzing the ontologies in GU.

Original languageEnglish
Pages (from-to)107-120
Number of pages14
JournalWeb Semantics
Volume7
Issue number2
DOIs
Publication statusPublished - 2009 Apr
Externally publishedYes

Keywords

  • Detecting innovative topics
  • Measuring similarity between ontologies
  • User-interest ontology

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Networks and Communications

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