Multi-Criteria Recommender Systems

نویسندگان

  • Gediminas Adomavicius
  • Nikos Manouselis
  • YoungOk Kwon
چکیده

This chapter aims to provide an overview of the class of multi-criteria recommender systems. First, it defines the recommendation problem as a multicriteria decision making (MCDM) problem, and reviews MCDM methods and techniques that can support the implementation of multi-criteria recommenders. Then, it focuses on the category of multi-criteria rating recommenders – techniques that provide recommendations by modelling a user’s utility for an item as a vector of ratings along several criteria. A review of current algorithms that use multi-criteria ratings for calculating predictions and generating recommendations is provided. Finally, the chapter concludes with a discussion on open issues and future challenges for the class of multi-criteria rating recommenders.

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تاریخ انتشار 2011