Structural and message based private friend recommendation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

The emerging growth of online social networks have opened new doors for various business applications such as promoting a new product across its customers. Besides this, friend recommendation is an important tool for recommending potential candidates as friends to users in order to enhance the development of the entire network structure. Existing friend recommendation methods utilize social network structure and/or user profile information. However, these techniques can no longer be applicable if the privacy of users is taken into consideration. In this paper, we propose a two-phase private friend recommendation protocol for recommending friends to a given target user based on the network structure as well as utilizing the real message interaction between users. Our protocol computes the recommendation scores of all users who are within a radius of h from the target user in a privacy preserving manner. In addition, we show the practical applicability of our approach through empirical analysis.

Original languageEnglish
Title of host publicationProceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012
Pages684-690
Number of pages7
DOIs
Publication statusPublished - 1 Dec 2012
Event2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012 - Istanbul, Turkey
Duration: 26 Aug 201229 Aug 2012

Other

Other2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012
CountryTurkey
CityIstanbul
Period26/08/1229/08/12

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Samanthula, B. K., & Jiang, W. (2012). Structural and message based private friend recommendation. In Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012 (pp. 684-690). [6425690] https://doi.org/10.1109/ASONAM.2012.114