Content area

Abstract

Recommender system is an emerging field of research with the advent of World Wide Web and E-commerce. Recently, an increasing usage of social networking websites plausibly has a great impact on diverse facets of our lives in different ways. Initially, researchers used to consider recommender system and social networks as independent topics. With the passage of time, they realized the importance of merging the two to produce enhanced recommendations. The integration of recommender system with social networks produces a new system termed as social recommender system. In this study, we initially describe the concept of recommender system and social recommender system and then investigates different features of social networks that play a major role in generating effective recommendations. Each feature plays an essential role in giving good recommendations and resolving the issues of traditional recommender systems. Lastly, this paper also discusses future work in this area that can aid in enriching the quality of social recommender systems.

Details

Title
A study on features of social recommender systems
Author
Shokeen Jyoti 1   VIAFID ORCID Logo  ; Rana Chhavi 1 

 University Institute of Engineering and Technology, M.D. University, Department of Computer Science and Engineering, Rohtak, India (GRID:grid.411524.7) (ISNI:0000 0004 1790 2262) 
Pages
965-988
Publication year
2020
Publication date
Feb 2020
Publisher
Springer Nature B.V.
ISSN
02692821
e-ISSN
15737462
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2172482474
Copyright
Artificial Intelligence Review is a copyright of Springer, (2019). All Rights Reserved.