Research Article
Personalized Recommender System: A Personal Recommender System Online Social Networking Sites
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 93 - Issue 9 |
| Published: May 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 },
year = { 2014 },
volume = { 93 },
number = { 9 },
pages = { 1-6 },
doi = { 10.5120/16240-5788 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2014
%A Hemant Kumar Kushwaha
%A J. Jeysree
%T Personalized Recommender System: A Personal Recommender System Online Social Networking Sites%T
%J International Journal of Computer Applications
%V 93
%N 9
%P 1-6
%R 10.5120/16240-5788
%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
- Developers, facebook
- Groups Google forum of Restfb
- Facebook4j
- Wikipedia
- Java for programmers, Detale Developers Series
- Vedran Podobnik, Darko Striga, Ana Jandras, Ignac Lovrek "How to Calculate Trust between Social Network Users?" University of Zagreb Faculty of Electrical Engineering and Computing Zagreb, Croatia
- Thomas DuBois, Jennifer Golbeck, and Aravind Srinivasan "Predicting Trust and Distrust in Social Networks" 2011 IEEE International Conference on Privacy, Security, Risk, and Trust, and IEEE International Conference on Social Computing.
- Sai T. Moturu, Jian Yang, Huan Liu "Quantifying Utility and Trustworthiness for Advice Shared on Online Social Media" 2009 International Conference on Computational Science and Engineering.
- 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.
- 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
Keywords