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Recommendation System: State of the Art Approach
by
Mohammad Aamir,
Mamta Bhusry
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 120 - Number 12 |
| Year of Publication: 2015 |
| Authors: Mohammad Aamir, Mamta Bhusry |
10.5120/21281-4200
|
Mohammad Aamir, Mamta Bhusry . Recommendation System: State of the Art Approach. International Journal of Computer Applications. 120, 12 ( June 2015), 25-32. DOI=10.5120/21281-4200
@article{
10.5120/21281-4200,
author = {
Mohammad Aamir,
Mamta Bhusry
},
title = { Recommendation System: State of the Art Approach },
journal = {
International Journal of Computer Applications
},
issue_date = { June 2015 },
volume = { 120 },
number = { 12 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = {
25-32
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume120/number12/21281-4200/
},
doi = { 10.5120/21281-4200 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:06:03.394102+05:30
%A Mohammad Aamir
%A Mamta Bhusry
%T Recommendation System: State of the Art Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 120
%N 12
%P 25-32
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract
A Recommender System (RS) is a composition of software tools and machine learning techniques that provides valuable piece of advice for items or services chosen by a user. Recommender systems are currently useful in both the research and in the commercial areas. Numerous approaches have been proposed for providing recommendations. Certainly, recommendation systems have an assortment of properties that may entail experiences of user such as user preference, prediction accuracy, confidence, trust, etc. In this paper we present a categorical reassess of the field of recommender systems and Approaches for Evaluation of Recommendation System to propose the recommendation method that would further help to enhance opinion mining through recommendations.
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Index Terms
Computer Science
Information Sciences
Keywords