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Efficiency Evaluation of Recommender Systems: Study of Existing Problems and Possible Extensions

Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 9)

Abstract

Recommender systems can help people to choose the desired product from a choice of various products. But there are various issues with the existing recommender systems. Thus, new systems which can efficiently recommend the most appropriate item to users based on their preferences are in demand. As a step towards providing the users with such a system, we present a general overview of the recommender systems in this paper. This paper also proposes potential solutions to the different problems which are found in current recommendation methods. These extensions to the current recommendation systems can improve their capabilities and make them appropriate for a broader area of applications. These potential extensions include integration of contextual information into the recommendation method, an improvement in understanding of items and users, developing less intrusive recommendation approaches, utilization of multi-criteria ratings, and providing more flexible types of recommendations.

Keywords

Contextual information Extensions to recommender systems Multi-criteria ratings Multidimensionality Recommender systems 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Amity UniversityNoidaIndia

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