CFP last date
22 April 2024
Call for Paper
May Edition
IJCA solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 22 April 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Friend Recommendation System for Online Social Networks

by Dagadu M. Jadhavar, V. R. Chirchi
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 153 - Number 12
Year of Publication: 2016
Authors: Dagadu M. Jadhavar, V. R. Chirchi
10.5120/ijca2016911963

Dagadu M. Jadhavar, V. R. Chirchi . Friend Recommendation System for Online Social Networks. International Journal of Computer Applications. 153, 12 ( Nov 2016), 1-3. DOI=10.5120/ijca2016911963

@article{ 10.5120/ijca2016911963,
author = { Dagadu M. Jadhavar, V. R. Chirchi },
title = { Friend Recommendation System for Online Social Networks },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2016 },
volume = { 153 },
number = { 12 },
month = { Nov },
year = { 2016 },
issn = { 0975-8887 },
pages = { 1-3 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume153/number12/26538-2016911963/ },
doi = { 10.5120/ijca2016911963 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:58:55.180658+05:30
%A Dagadu M. Jadhavar
%A V. R. Chirchi
%T Friend Recommendation System for Online Social Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 153
%N 12
%P 1-3
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The Already social networking services recommends friends list to requesting user that is based on their social graphs, but they cannot fulfill user need to user preferences on friend selection. In this paper, we represent Friend recommendation, as lifestyle based friend recommendation system for social networks. Collecting data from smartphone sensors and identifying lifestyle of user, if lifestyle having high score similarities then recommend friend to user. Here probability Distribution algorithm is used for extracting lifestyle of users learns from text mining. Also use the Activity recognition for classify the activity of user and propose a similarity metric to find the similarity of life styles between users, and after this one finding user’s impact in consideration of life styles with a friend-matching graph. User request is received then friend recommendation system gives response as similar lifestyle matching friends lists to user query. At last, Friend recommendation system uses the feedback modules to improve the recommendation accuracy. We have Friend recommendation system is to implemented on the Android-based smartphones, By using Friend recommendation system user can get best friend list for preferences of users in choosing friends.

References
  1. Zhibo Wang ,Student member, IEEE, Jilong Liao, Qing Cao, Member, IEEE, Hairong Qi, Senior Member ,IEEE , and Zhi Wang ,Member, IEEE” FriendBook:A Semantic Based Friend Recommendation System for Social Networks” EEE Transaction on mobile computing, VOL.14,No.3,MARCH 2015.
  2. Facebookstatistics. http://www.digitalbuzzblog.com/ facebook-statistics-stats-facts-2011/.
  3. L. Bian and H. Holtzman. Online friend recommendation through personality matching and collaborative filtering. Proc. of UBICOMM, pages 230-235, 2011.
  4. T. Huynh, M. Fritz and B. Schiel. Discovery of Activity Patterns using Topic Models. Proc. of Ubi Comp. 2008.
  5. K. Farrahi and D. Gatica-Perez. Probabilistic mining of socio-geographic routines from mobile phone data. Selected Topics in Signal Processing, IEEE Journal of, Vol. 4, No. 4, pp. 746-755, 2010.
  6. C. M. Bishop. Pattern recognition and machine learning. Springer New York, 2006.
  7. P. Desikan, N. Pathak, J. Srivastava, and V. Kumar. Incremental page rank computation on evolving graphs. Proc. of WWW, pages 1094-1095, 2005.
  8. J. Kwon and S. Kim. Friend recommendation method using physical and social context. International Journal of Computer Science and Network Security, 10(11):116-120, 2010.
  9. E. Miluzzo, N. D. Lane, S. B. Eisenman, and A. T. Campbell. Cenceme-Injecting Sensing Presence into Social Networking Applications. Proc. of EuroSSC, pages 1-28, October 2007.
  10. Y. Zheng, Y. Chen, Q. Li, X. Xie, and W.-Y. Ma. Understanding Transportation Modes Based on GPS Data for Web Applications. ACM Transactions on the Web (TWEB), 4(1):1-36, 2010.
  11. J. Biagioni, T. Gerlich, T. Merrifield, and J. Eriksson. EasyTracker: Automatic Transit Tracking, Mapping, and Arrival Time Prediction Using Smartphones. Proc. of SenSys, pages 68-81, 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Life style Friend Bag of Activity model Social Networks Similarity Metric.

Powered by PhDFocusTM