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Artificial Intelligence Review

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29.01.2019

A study on features of social recommender systems

verfasst von: Jyoti Shokeen, Chhavi Rana

Erschienen in: Artificial Intelligence Review | Ausgabe 2/2020

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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.

Vorheriger Artikel A meta-heuristic proposal for inverse kinematics solution of 7-DOF serial robotic manipulator: quantum behaved particle swarm algorithm

Nächster Artikel The state of the art and taxonomy of big data analytics: view from new big data framework

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Titel: A study on features of social recommender systems
verfasst von: Jyoti Shokeen
Chhavi Rana
Publikationsdatum: 29.01.2019
Verlag: Springer Netherlands
Erschienen in: Artificial Intelligence Review / Ausgabe 2/2020
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI: https://doi.org/10.1007/s10462-019-09684-w

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