Detecting innovative topics based on user-interest ontology

Authors:
Makoto Nakatsuji;Makoto Yoshida;Toru Ishida
Affiliations:
NTT Cyber Solutions Laboratories, NTT Corporation, 1-1, Hikarinooka, Yokosuka-Shi, Kanagawa 239-0847, Japan;Data Center Facilities Department, NTT Facilities Inc., Granpark Tower, 3-4-1, Shibaura, Minato-ku, Tokyo 108-0023, Japan;Department of Social Informatics, Kyoto University, Kyoto 606-8501, Japan
Venue:
Web Semantics: Science, Services and Agents on the World Wide Web
Year:
2009

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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 G"U that has high similarity to user u. The innovative topics for u are then detected by determining a suitable size of G"U and analyzing the ontologies in G"U.