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Survey on Recommendation System

by Lipi Shah, Hetal Gaudani, Prem Balani
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 137 - Number 7
Year of Publication: 2016
Authors: Lipi Shah, Hetal Gaudani, Prem Balani
10.5120/ijca2016908821

Lipi Shah, Hetal Gaudani, Prem Balani . Survey on Recommendation System. International Journal of Computer Applications. 137, 7 ( March 2016), 43-49. DOI=10.5120/ijca2016908821

@article{ 10.5120/ijca2016908821,
author = { Lipi Shah, Hetal Gaudani, Prem Balani },
title = { Survey on Recommendation System },
journal = { International Journal of Computer Applications },
issue_date = { March 2016 },
volume = { 137 },
number = { 7 },
month = { March },
year = { 2016 },
issn = { 0975-8887 },
pages = { 43-49 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume137/number7/24291-2016908821/ },
doi = { 10.5120/ijca2016908821 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:37:46.899941+05:30
%A Lipi Shah
%A Hetal Gaudani
%A Prem Balani
%T Survey on Recommendation System
%J International Journal of Computer Applications
%@ 0975-8887
%V 137
%N 7
%P 43-49
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper describes the overview of recommendation system. The recommendation system is the sub-part of the data mining field. This is the era of the e-commerce business. Recommender systems are used to assists the enterprise to implement one-to-one marketing strategies. These type of strategies offer several advantages like establishing the customer loyalty, increase the probability of cross-selling, fulfilling the customer need by presenting the items or products of customer interest. The recommendation system (RS) is crucial in many applications on the web. The recommendation system is mainly classified into following three categories: content-based, collaborative-based and hybrid approaches. Different categories have its own advantages as well as disadvantages .This paper describes the different techniques in each category and the issues in each category.

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Index Terms

Computer Science
Information Sciences

Keywords

Recommendation system content based filtering collaborative filtering hybrid approach.

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