Long-term user engagement in recommender systems: a review

Swathi Edem, B. V. Ram Naresh Yadav

Abstract


The purpose of recommender systems (RS) is to facilitate user collaboration and communication on the platform. Nevertheless, there is limited knowledge regarding the extent of this relationship and the techniques by which RS could promote persistent user engagement with the platform. In order to fill this void, the present study investigates the role of RS in transforming users’ short-term engagement with the RS into long-lasting involvement with the platform. We present a theoretical framework by reviewing relevant literature in the domains of RS and user engagement to probe these issues. We provide open challenges in this field along with metrics in the present study.

Keywords


Long-term metrics; Recommender systems; Reinforcement learning; User engagement; User satisfaction

Full Text:

PDF


DOI: http://doi.org/10.11591/ijeecs.v38.i3.pp2050-2058

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES).

shopify stats IJEECS visitor statistics