Item reputation-aware recommender systems
Autor: | Yue Xu, Nan Tian, Ahmad Abdel-Hafez |
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Rok vydání: | 2014 |
Předmět: |
Information retrieval
User profile Computer science media_common.quotation_subject Reputation System Recommender system 080704 Information Retrieval and Web Search Personalized Reputation World Wide Web Order (business) Reputation system Merging Ranked Lists 080605 Decision Support and Group Support Systems Recommender System Quality (business) Reputation media_common |
Zdroj: | IIWAS '14 : Proceedings of International Conference on Information Integration and Web-based Applications & Services iiWAS |
ISSN: | 2381-3652 |
Popis: | Recommender systems provide personalized advice for online customers based on their own preferences, while reputation systems generate a community advice on the quality of items on the Web. Both systems employ users' ratings to generate their output. In this paper, we aim to combine reputation models with recommender systems to enhance the accuracy of recommendations. Our proposed methods make two contributions. First of all, we propose two methods for merging two ranked item lists which are generated based on recommendation scores and reputation scores, respectively. In addition, a novel personalized reputation method is designed in order to generate item reputations based upon users' interests. The proposed merging methods can be applicable to any recommendation methods and reputation methods, i.e., they are independent from generating recommendation scores and reputation scores. The experiments we conducted showed that the proposed methods could enhance the accuracy of existing recommender systems. |
Databáze: | OpenAIRE |
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