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Using personality to adjust diversity in recommender systems

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Published:01 May 2013Publication History

ABSTRACT

Nowadays, although some approaches have been proposed to enhance the diversity in online recommendations, they neglect the user's spontaneous needs that might be possibly influenced by her/his personality. Previously, we did a user survey that showed some personality dimensions (such as conscientiousness which is one of personality factors according to the big-five factor model) have significant impact not only on users' diversity preference over items' individual attributes, but also on their overall diversity needs when all attributes are combined. Motivated by the findings, in the current work, we propose a strategy that explicitly embeds personality, as a moderating factor, to adjust the diversity degree within multiple recommendations. Moreover, we performed a user evaluation on the developed system. The experimental results demonstrate an effective solution to generate personality-based diversity in recommender systems.

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            cover image ACM Conferences
            HT '13: Proceedings of the 24th ACM Conference on Hypertext and Social Media
            May 2013
            275 pages
            ISBN:9781450319676
            DOI:10.1145/2481492

            Copyright © 2013 ACM

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            Publication History

            • Published: 1 May 2013

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            HT '13 Paper Acceptance Rate16of96submissions,17%Overall Acceptance Rate378of1,158submissions,33%

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