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Reseach Article

A Review on Current Recommendation Systems

by Shivani Sharma, Manish Dhir
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 131 - Number 13
Year of Publication: 2015
Authors: Shivani Sharma, Manish Dhir
10.5120/ijca2015907500

Shivani Sharma, Manish Dhir . A Review on Current Recommendation Systems. International Journal of Computer Applications. 131, 13 ( December 2015), 7-11. DOI=10.5120/ijca2015907500

@article{ 10.5120/ijca2015907500,
author = { Shivani Sharma, Manish Dhir },
title = { A Review on Current Recommendation Systems },
journal = { International Journal of Computer Applications },
issue_date = { December 2015 },
volume = { 131 },
number = { 13 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = { 7-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume131/number13/23507-2015907500/ },
doi = { 10.5120/ijca2015907500 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:27:13.242919+05:30
%A Shivani Sharma
%A Manish Dhir
%T A Review on Current Recommendation Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 131
%N 13
%P 7-11
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In recent years, E-commerce, web service and web information system have been used explosively. Massive explosion of the world-wide-web and the emergence of e- commerce have encouraged designers to develop recommendation systems. Web users demonstrate a variety of navigational patterns by clicking series of web pages. These patterns can be understood by mining user logs using WUM. One of the widely used applications of Web Usage Mining is Online Recommendation and prediction. Generally, all the recommendation systems follow a framework for generating efficient recommendations. Various recommendation systems use different approaches based on the sources of information they utilize. The accessible sources are user information (demographics), the product information (keywords, genres) and the user-item ratings. This paper gives introductive information about recommendation system, their techniques, and algorithms and also describes some existing works.

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Index Terms

Computer Science
Information Sciences

Keywords

Recommendation System Knowledge based systems Web Usage Mining.