ISSN 2071-8594

Russian academy of sciences

Editor-in-Chief

Gennady Osipov

A .V. Smirnov, A. V. Ponomarev Multi-Criteria Context-Driven Recommender Systems: Model and Method

Abstract.

A model and method of generating context-driven recommendations for recommendation systems with multi-criteria ratings are proposed, applicable when the user's attitude to the object is fixed not by using one integral criterion (assessment, overall rating), but by using a set of individual criteria that evaluate different aspects of the object. The proposed model and method allow to solve two main problems of using recommender systems: to rank objects according to the predicted subjective integral utility with given weights of partial criteria and to rank objects according to the predicted subjective integral utility in a given context.

Keywords:

recommendation systems, recommender systems, multi-criteria optimization, weighted sum method, collaborative filtering, content filtering, context-driven systems.

PP. 24-31.

DOI 10.14357/20718594190303

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