Evaluation of recommender systems: A multi-criteria decision making approach

نویسندگان

  • Babak Sohrabi
  • Mehdi Toloo
  • Ali Moeini
  • Soroosh Nalchigar
چکیده

The evaluation and selection of recommender systems is a difficult decision making process. This difficulty is partially due to the large diversity of published evaluation criteria in addition to lack of standardized methods of evaluation. As such, a systematic methodology is needed that explicitly considers multiple, possibly conflicting metrics and assists decision makers to evaluate and find the best recommender system among a given set of alternatives. This paper introduces MultiCriteria Decision Making (MCDM) approach for evaluation of recommender systems. In particular, this paper proposes the use of Data Envelopment Analysis (DEA) approach, as a sub-category of MCDM, in order to solve this problem. Various DEA models are introduced and their applicability are illustrated. A real case of evaluation of recommender systems is used to demonstrate the approach.

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تاریخ انتشار 2004