Personalized Search Based on a User-Centered Recommender Engine

Designing personalized search engines based on a recommender system that takes into consideration the user situated moment in relation to the subject matter and the context that governs user interest has been largely ignored. In this paper, we present a novel approach to integrating user interests i...

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Bibliographic Details
Published in2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Vol. 1; pp. 200 - 203
Main Authors Zhuhadar, Leyla, Nasraoui, Olfa
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2010
Subjects
ontology
recommender search engine
semantic
user relevance feedback
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Summary:Designing personalized search engines based on a recommender system that takes into consideration the user situated moment in relation to the subject matter and the context that governs user interest has been largely ignored. In this paper, we present a novel approach to integrating user interests into search within a recommender system that is guided by the semantic representation of the user and the content. In addition, our research tackles two problems of creating any recommender system: (a) the initial stage problem (how to provide recommendations to a user if the system hasn't been used yet) and (b) user context (providing the same user with different recommendations based on the context of their recent activity). Also the design of our recommender system is modular. It integrates and accommodates user's preferences by using User Relevance Feedback. Finally, we describe how the personalization aspects can increase the recommendation quality.
ISBN:9781424484829
1424484820
DOI:10.1109/WI-IAT.2010.296