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A Survey of Recommendation Systems

Sushma Malik, Anamika Rana, Mamta Bansal

Source Title: Information Resources Management Journal (IRMJ)33(4)

ISSN: 1040-1628|EISSN: 1533-7979|EISBN13: 9781799804765|DOI: 10.4018/IRMJ.2020100104

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MLA

Malik, Sushma, et al. "A Survey of Recommendation Systems." IRMJ vol.33, no.4 2020: pp.53-73. http://doi.org/10.4018/IRMJ.2020100104

APA

Malik, S., Rana, A., & Bansal, M. (2020). A Survey of Recommendation Systems. Information Resources Management Journal (IRMJ), 33(4), 53-73. http://doi.org/10.4018/IRMJ.2020100104

Chicago

Malik, Sushma, Anamika Rana, and Mamta Bansal. "A Survey of Recommendation Systems," Information Resources Management Journal (IRMJ) 33, no.4: 53-73. http://doi.org/10.4018/IRMJ.2020100104

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Abstract

Today's internet is able to discover almost any product or piece of information. The large amounts of unfiltered information returned by an internet query calls for filters able to validate and rank the available options. Recommender systems (RSs) are a software tool designed to qualify the options available and make suggestions that align with the user's requirements and expectations. This paper reviews some significant applications of RSS in various areas like videos, music, eCommerce sites, news, and many more. It also reviews various filtering techniques like collaborative, content based, and hybrid.

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A Survey of Recommendation Systems

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