Litcius/Paper detail

Recommender systems: an overview, research trends, and future directions

Pradeep Kumar Singh, Prasenjit Choudhury, Avick Kumar Dey, Pijush Kanti Dutta Pramanik

2020International Journal of Business and Systems Research36 citationsDOI

Abstract

Recommender system (RS) has emerged as a major research interest that aims to help users to find items online by providing suggestions that closely match their interest. This paper provides a comprehensive study on the RS covering the different recommendation approaches, associated issues, and techniques used for information retrieval. Thanks to its widespread applications, it has induced research interest among a significant number of researchers around the globe. The main purpose of this paper is to spot the research trend in RS. More than 1,000 research papers, published by ACM, IEEE, Springer, and Elsevier since 2011 to the first quarter of 2017, have been considered. Several interesting findings have come out of this study, which will help the current and future RS researchers to assess and set their research roadmap. Furthermore, this paper also envisions the future of RS which may open up new research directions in this domain.

Topics & Concepts

Recommender systemGlobeComputer scienceData scienceDomain (mathematical analysis)Quarter (Canadian coin)Open researchSet (abstract data type)World Wide WebPsychologyMathematicsProgramming languageNeuroscienceArchaeologyHistoryMathematical analysisRecommender Systems and TechniquesSentiment Analysis and Opinion MiningMachine Learning and ELM
Recommender systems: an overview, research trends, and future directions | Litcius