CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 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

A Review on Trust-Aware and Privacy Preserving Profile Matching System for Personalized User Recommendations in Social networks

by Kulkarni Vaishnavi Shripad, Archana S. Vaidya
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 104 - Number 12
Year of Publication: 2014
Authors: Kulkarni Vaishnavi Shripad, Archana S. Vaidya
10.5120/18254-9335

Kulkarni Vaishnavi Shripad, Archana S. Vaidya . A Review on Trust-Aware and Privacy Preserving Profile Matching System for Personalized User Recommendations in Social networks. International Journal of Computer Applications. 104, 12 ( October 2014), 22-25. DOI=10.5120/18254-9335

@article{ 10.5120/18254-9335,
author = { Kulkarni Vaishnavi Shripad, Archana S. Vaidya },
title = { A Review on Trust-Aware and Privacy Preserving Profile Matching System for Personalized User Recommendations in Social networks },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 104 },
number = { 12 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 22-25 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume104/number12/18254-9335/ },
doi = { 10.5120/18254-9335 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:36:30.128838+05:30
%A Kulkarni Vaishnavi Shripad
%A Archana S. Vaidya
%T A Review on Trust-Aware and Privacy Preserving Profile Matching System for Personalized User Recommendations in Social networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 104
%N 12
%P 22-25
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Trust is becoming a very important part of social network from the security point of view. In this project, we introduce a framework for handling trust in social networks, which is based on reputation mechanism. The reputation mechanism captures the implicit and explicit connections between the network members, analyses the semantics and dynamics of these connections, and provides personalized user recommendations to the network members. Based on the trust semantics, the system will provide the positive (trustworthy) recommendations and the negative (untrustworthy) recommendations. Along with this our system provides one more interesting mode i. e. public profile matching that preserves privacy on social networks. This profile matching contributes in reputation ratings required for suggestions of friend list. In order to compute the reputation of each member, we adopt several other properties of trust such as, transitivity, personalization, and context, and draw ideas from sociology axioms. Trust is not perfectly transitive in social networks, in that trust decays along the transition path, but it is generally agreed that it can be communicated between people. Along with trust generation percentile of profile matching is also considered for personal recommendation.

References
  1. Magdalini Eirinaki, Malamati D. Louta,Member, IEEE,and Iraklis Varlamis,Member, IEEE. "A Trust-Aware System for Personalized User Recommendations in Social Networks" IEEE Trans. Systems, Man, And Cybernetics: Systems, Vol. 44, No. 4, pp. 409 – 421 APRIL 2014
  2. Ming Li, Member, IEEE, Shucheng Yu, Member, IEEE, Ning Cao, Student Member, IEEE, and Wenjing Lou, Senior Member, IEEE. "Privacy-Preserving Distributed Profile Matching in Proximity-based Mobile Social Networks" IEEE Trans. Wireless Communications Vol. : 12 No. : 5 pp. 2024 - 2033 Year 2013
  3. I. Guy, N. Zwerdling, D. Carmel, I. Ronen, E. Uziel, S. Yogev, and S. Ofek-Koifman, "Personalized recommendation of social software items based on social relations," in Proc. 3rd ACM Conf. Recommender Syst. , 2009, pp. 53-60.
  4. J. Leskovec, D. P. Huttenlocher, and J. M. Kleinberg, "Predicting positive and negative links in online social networks," inProc. 19th Int. Conf. World Wide Web, 2010, pp. 641-650.
  5. J. Chen, W. Geyer, C. Dugan, M. J. Muller, and I. Guy, "Make new friends, but keep the old: Recommending people on social networking sites," in Proc. SIGCHI Conf. Human Factors Comput. Syst. , 2009, pp. 201-210.
  6. I. Konstas, V. Stathopoulos, and J. M. Jose, "On social networks and collaborative recommendation," in Proc. 32nd Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval, 2009, pp. 195-202.
  7. I. Varlamis, M. Eirinaki, and M. D. Louta, "Application of social network metrics to a trust-aware collaborative model for generating personalized user recommendations," in The Influence of Technology on Social Network Analysis and Mining(Lecture Notes in Social Networks Series), vol. 6, T. Ozyer, J. G. Rokne, G. Wagner, and A. H. P. Reuser, Eds. Berlin, Germany: Springer, 2013, pp. 49-74.
  8. I. Guy, I. Ronen, and E. Wilcox, "Do you know? : Recommending people to invite into your social network," in Proc. 14th Int. Conf. Intell. User Interfaces, 2009, pp. 77-86.
  9. J. Golbeck, "Trust and nuanced profile similarity in online social networks,"J. ACM Trans. Web, vol. 3, no. 4, pp. 1–33, 2009.
  10. T. Grandison and M. Sloman, "A survey of trust in internet applications," IEEE Commun. Surveys Tuts. , vol. 3, no. 4, pp. 2–16, Oct. 2000.
  11. J. Kunegis, A. Lommatzsch, and C. Bauckhage, "The slashdot zoo: Mining a social network with negative edges," inProc. 18th Int. Conf. World Wide Web, 2009, pp. 741–750.
Index Terms

Computer Science
Information Sciences

Keywords

Social Networks Reputation Personalisation Trust Recommendation Profile Matching.

Powered by PhDFocusTM