Trust-based recommendations for documents

Issue title: Recommender Systems

Article type: Research Article

Authors: Hess, Claudia | Schlieder, Christoph

Affiliations: Laboratory for Semantic Information Technology, University of Bamberg, 96045 Bamberg, Germany. E-mails: {claudia.hess, christoph.schlieder}@uni-bamberg.de

Abstract: Recommendation techniques that analyze social trust networks attracted much attention in the last few years. They recommend such items that are appreciated by trusted friends. In this paper, we explore how to use trust information for generating personalized document recommendations such as for scientific papers or for webpages. The basic idea is to jointly analyze a trust network between readers who review the documents and the reference network between the documents. We develop trust-enhanced visibility measures for measuring the quality and the importance of documents and evaluate them in simulation studies.

Keywords: Trust-based recommendations, recommender systems, trust networks, document reference networks, personalization

DOI: 10.3233/AIC-2008-0432

Journal: AI Communications, vol. 21, no. 2-3, pp. 145-153, 2008