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

Author

Listed:
  • Pradeep Kumar Singh
  • Pijush Kanti Dutta Pramanik
  • Avick Kumar Dey
  • Prasenjit Choudhury

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.

Suggested Citation

  • Pradeep Kumar Singh & Pijush Kanti Dutta Pramanik & Avick Kumar Dey & Prasenjit Choudhury, 2021. "Recommender systems: an overview, research trends, and future directions," International Journal of Business and Systems Research, Inderscience Enterprises Ltd, vol. 15(1), pages 14-52.
    • Handle: RePEc:ids:ijbsre:v:15:y:2021:i:1:p:14-52
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    Cited by:

    1. Farah Tawfiq Abdul Hussien & Abdul Monem S. Rahma & Hala B. Abdulwahab, 2021. "An E-Commerce Recommendation System Based on Dynamic Analysis of Customer Behavior," Sustainability, MDPI, vol. 13(19), pages 1-21, September.

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