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Recommender Systems

Surveys recommender systems, their types, problems, and future directions from over 1,000 papers published 2011 to early 2020.

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Recommender Systems

By C. Lucchese, Cristina Ioana Muntean, Raffaele Perego et al.Wirtschaftsinf.
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This paper is a survey that offers an overview of recommender systems, describing the different types of RS, the problems that arise in them, and the future scope of the field. Its core purpose is to spot research trends, and to do so it considers more than 1,000 research papers published by ACM, IEEE, Elsevier, and Springer between 2011 and the first quarter of 2020.

In reviewing this large body of work, the authors report several interesting findings meant to help current and future recommender system researchers assess the landscape and set their own research roadmaps. The paper additionally envisions the future of recommender systems, suggesting directions that may open up new lines of research in the domain.

Abstract

This paper provides an overview of recommender systems (RS), covering their types, common problems, and future scope. Its main aim is to identify research trends in RS, drawing on more than 1,000 research papers published by ACM, IEEE, Elsevier, and Springer from 2011 through the first quarter of 2020. The review surfaces several interesting findings intended to help current and future researchers assess and set their research roadmaps. It also envisions the future of recommender systems and potential new research directions.

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