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Recommender System: Review

by Akshita, Smita
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 71 - Number 24
Year of Publication: 2013
Authors: Akshita, Smita
10.5120/12693-9180

Akshita, Smita . Recommender System: Review. International Journal of Computer Applications. 71, 24 ( June 2013), 38-42. DOI=10.5120/12693-9180

@article{ 10.5120/12693-9180,
author = { Akshita, Smita },
title = { Recommender System: Review },
journal = { International Journal of Computer Applications },
issue_date = { June 2013 },
volume = { 71 },
number = { 24 },
month = { June },
year = { 2013 },
issn = { 0975-8887 },
pages = { 38-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume71/number24/12693-9180/ },
doi = { 10.5120/12693-9180 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:36:37.309209+05:30
%A Akshita
%A Smita
%T Recommender System: Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 71
%N 24
%P 38-42
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

One of the major data mining applications is Recommender System. It is the intelligent system that basically investigate the dataset present in existing system and based on which it will give some suggestions to the user regarding further process. This paper discuss various techniques proposed for recommendations including content based, collaborative based and other techniques. To improve performance, these methods have sometimes been combined in hybrid recommenders. It also discuss about growing area of research in the area of recommender systems that is mobile recommender systems.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Recommender system Content based Collaborative based Data mining Hybrid Recommender System

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