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Reseach Article

Personalized Recommender System: A Personal Recommender System Online Social Networking Sites

by Hemant Kumar Kushwaha, J. Jeysree
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 93 - Number 9
Year of Publication: 2014
Authors: Hemant Kumar Kushwaha, J. Jeysree
10.5120/16240-5788

Hemant Kumar Kushwaha, J. Jeysree . Personalized Recommender System: A Personal Recommender System Online Social Networking Sites. International Journal of Computer Applications. 93, 9 ( May 2014), 1-6. DOI=10.5120/16240-5788

@article{ 10.5120/16240-5788,
author = { Hemant Kumar Kushwaha, J. Jeysree },
title = { Personalized Recommender System: A Personal Recommender System Online Social Networking Sites },
journal = { International Journal of Computer Applications },
issue_date = { May 2014 },
volume = { 93 },
number = { 9 },
month = { May },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume93/number9/16240-5788/ },
doi = { 10.5120/16240-5788 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:15:19.916252+05:30
%A Hemant Kumar Kushwaha
%A J. Jeysree
%T Personalized Recommender System: A Personal Recommender System Online Social Networking Sites
%J International Journal of Computer Applications
%@ 0975-8887
%V 93
%N 9
%P 1-6
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Recommender system for online marketing site plays a key role for the e-marketing or purchase made online by consumers. As there are many recommendations for a particular keyword, determining which recommendations have higher impact for a particular user is difficult. So it is useful to make a personal recommender based on the user preferences may helpful in solving such a problems and can deliver a good search result. Based on user actions (preferences, like) within a close group like any networking site a best personalized recommender can be designed. As the growing popularity of www every things going to b dependent on the virtual world, e-commerce and e-advertisement are the very important aspect of them, the growing popularity of www also leaded to virtualized one's friend. So this work is defining a approach in which the personal relationships between friends is calculated after that this calculation can be used to determine the good recommender for a particular user based on his/her friends reviews and the his/her preferences.

References
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  9. Xiaoxin Yin, Jiawei Han Senior Member IEEE, and Philip S. Yu Fellow IEEE "Truth Discovery with Multiple Conflicting Information Providers on the Web" IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 20, NO. 6, JUNE 2008.
  10. Hemant Kumar Kushwaha M. Tech. Scholar, Ms. J. Jeysree Assistnat Professor Department of Information Technology, Faculty of Engineering and Technology, SRM University, Kattankulathur-603203, India "Trust_System How to know which fact is revelent and useful within a social networking site. " 2014 IJEDR Volume 2, Issue 1 ISSN: 2321-9939
Index Terms

Computer Science
Information Sciences

Keywords

Trust Trust_Friend Recommender Trust metrics ego user close-nest.