Interest-driven private friend recommendation

Research output: Contribution to journalArticleResearchpeer-review

8 Citations (Scopus)

Abstract

The emerging growth of online social networks has opened new doors for various kinds of applications such as business intelligence and expanding social connections through friend recommendations. In particular, friend recommendation facilitates users to explore new friendships based on social network structures, user profile information (similar interest) or both. However, as the privacy concerns of users are on the rise, searching for new friends is not a straightforward task under the assumption that users’ information is kept private. Along this direction, this paper proposes two private friend recommendation algorithms based on the social network structure and the users’ social tags. The first protocol is more efficient from a user’s perspective compared to the second protocol, and this efficiency gain comes at the expense of relaxing the underlying privacy assumptions. On the other hand, the second protocol provides the best security guarantee. In addition, we empirically analyze the complexities of the proposed protocols and provide various experimental results.

Original languageEnglish
Pages (from-to)663-687
Number of pages25
JournalKnowledge and Information Systems
Volume42
Issue number3
DOIs
StatePublished - 1 Jan 2013

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Competitive intelligence

Keywords

  • Friend recommendation
  • Privacy
  • Social tags

Cite this

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title = "Interest-driven private friend recommendation",
abstract = "The emerging growth of online social networks has opened new doors for various kinds of applications such as business intelligence and expanding social connections through friend recommendations. In particular, friend recommendation facilitates users to explore new friendships based on social network structures, user profile information (similar interest) or both. However, as the privacy concerns of users are on the rise, searching for new friends is not a straightforward task under the assumption that users’ information is kept private. Along this direction, this paper proposes two private friend recommendation algorithms based on the social network structure and the users’ social tags. The first protocol is more efficient from a user’s perspective compared to the second protocol, and this efficiency gain comes at the expense of relaxing the underlying privacy assumptions. On the other hand, the second protocol provides the best security guarantee. In addition, we empirically analyze the complexities of the proposed protocols and provide various experimental results.",
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Interest-driven private friend recommendation. / Samanthula, Bharath Kumar; Jiang, Wei.

In: Knowledge and Information Systems, Vol. 42, No. 3, 01.01.2013, p. 663-687.

Research output: Contribution to journalArticleResearchpeer-review

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AU - Samanthula, Bharath Kumar

AU - Jiang, Wei

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