A Survey of Recommendation Systems

A Survey of Recommendation Systems

Sushma Malik, Anamika Rana, Mamta Bansal
Copyright: © 2020 |Pages: 21
DOI: 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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2. Phases Of Recommendation Process

Recommender System digs out the significant information from the huge amount of overload information which is collected according to the customer’s preferences and likes. For the recommendation of products or items to the customers, RS follows three main phases for the recommendation process like the Information collection phase, Learning phase, Prediction/Recommendation phase. The phases of the recommendation system are shown in Figure 1.

Figure 1.

Phases of recommendation process

IRMJ.2020100104.f01
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3. Approaches Of Recommender System

An RS can be designed with many techniques. This section includes the main recommendation techniques, showing in Figure 2 (A & Biradar, 2016).

Figure 2.

Approaches of recommender system

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