Reputation-Enhanced Recommender Systems

Abstract : Recommender systems are pivotal components of modern Internet platforms and constitute a well-established research field. By now, research has resulted in highly sophisticated recommender algorithms whose further optimization often yields only marginal improvements. This paper goes beyond the commonly dominating focus on optimizing algorithms and instead follows the idea of enhancing recommender systems with reputation data. Since the concept of reputation-enhanced recommender systems has attracted considerable attention in recent years, the main aim of the paper is to provide a comprehensive survey of the approaches proposed so far. To this end, existing work are identified by means of a systematic literature review and classified according to carefully considered dimensions. In addition, the resulting structured analysis of the state of the art serves as a basis for the deduction of future research directions.
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Communication dans un congrès
Jan-Philipp Steghöfer; Babak Esfandiari. 11th IFIP International Conference on Trust Management (TM), Jun 2017, Gothenburg, Sweden. Springer International Publishing, IFIP Advances in Information and Communication Technology, AICT-505, pp.163-179, 2017, Trust Management XI. 〈10.1007/978-3-319-59171-1_13〉
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Christian Richthammer, Michael Weber, Günther Pernul. Reputation-Enhanced Recommender Systems. Jan-Philipp Steghöfer; Babak Esfandiari. 11th IFIP International Conference on Trust Management (TM), Jun 2017, Gothenburg, Sweden. Springer International Publishing, IFIP Advances in Information and Communication Technology, AICT-505, pp.163-179, 2017, Trust Management XI. 〈10.1007/978-3-319-59171-1_13〉. 〈hal-01651165〉

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