Mathematics of Distances and Applications 103 METRIC BASED RECOMMENDER SYSTEMS

نویسندگان

  • Ali Akhtarzada
  • Cristian S. Calude
  • John Hosking
چکیده

Information overload and an abundance of choices create situations where selecting one option becomes extremely difficult or even worse, a guessing game. Collaborative ranking systems address this problem by creating intelligent rankings of items based on user opinions aggregation. This paper presents a metric-based multi-criteria recommender system that can be used on non-rigid sets of criteria. These systems fare well with respect to accuracy, transparency and flexibility.

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تاریخ انتشار 2012