A study on features of social recommender systems

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.

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Fig. 1

Notes

  1. 1.

    https://www.amazon.com.

  2. 2.

    https://www.netflix.com.

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Acknowledgements

The first author of the paper likes to say thanks to Council of Scientific and Industrial Research (CSIR) to receive financial assistance in the form of JRF.

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Correspondence to Jyoti Shokeen.

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Shokeen, J., Rana, C. A study on features of social recommender systems. Artif Intell Rev 53, 965–988 (2020). https://doi.org/10.1007/s10462-019-09684-w

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Keywords

  • Recommender system
  • Social recommender system
  • Cold-start
  • Collaborative filtering
  • Social networks
  • Information overload