Evolutionary computing in recommender systems: a review of recent research

Horváth, Tomáš; de Carvalho, André C. P. L. F.

Abstract

One of the main current applications of intelligent systems is recommender systems (RS). RS can help users to find relevant items in huge information spaces in a personalized way. Several techniques have been investigated for the development of RS. One of them is evolutionary computational (EC) techniques, which is an emerging trend with various application areas. The increasing interest in using EC for web personalization, information retrieval and RS fostered the publication of survey papers on the subject. However, these surveys have analyzed only a small number of publications, around ten. This study provides a comprehensive review of more than 65 research publications focusing on five aspects we consider relevant for such: the recommendation technique used, the datasets and the evaluation methods adopted in their experimental parts, the baselines employed in the experimental comparison of proposed approaches and the reproducibility of the reported experiments. At the end of this review, we discuss negative and positive aspects of these papers, as well as point out opportunities, challenges and possible future research directions. To the best of our knowledge, this review is the most comprehensive review of various approaches using EC in RS. Thus, we believe this review will be a relevant material for researchers interested in EC and RS.

Citation

Horváth, T., & de Carvalho, A. C. P. L. F. (2017). Evolutionary computing in recommender systems: a review of recent research. Natural Computing, 16(3), 441-462. https://doi.org/10.1007/s11047-016-9540-y

• Journal Article Type: Review
• Acceptance Date: Dec 27, 2015
• Online Publication Date: Jan 18, 2016
• Publication Date: 2017
• Deposit Date: Mar 27, 2024
• Journal: Natural Computing
• Print ISSN: 1567-7818
• Electronic ISSN: 1572-9796
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 16
• Issue: 3
• Pages: 441-462
• DOI: https://doi.org/10.1007/s11047-016-9540-y
• Keywords: Evolutionary computing, Genetic algorithms, Genetic programming, Recommender systems, Personalization
• Public URL: http://researchrepository.napier.ac.uk/Output/3577520