In tags we trust

Trust modeling in social tagging of multimedia content

Ivan Ivanov, Peter Vajda, Jong-Seok Lee, Touradj Ebrahimi

Research output: Contribution to journalReview article

18 Citations (Scopus)

Abstract

Tagging in online social networks is very popular these days, as it facilitates search and retrieval of multimedia content. However, noisy and spam annotations often make it difficult to perform an efficient search. Users may make mistakes in tagging and irrelevant tags and content may be maliciously added for advertisement or self-promotion. This article surveys recent advances in techniques for combatting such noise and spam in social tagging. We classify the state-of-the-art approaches into a few categories and study representative examples in each. We also qualitatively compare and contrast them and outline open issues for future research.

Original languageEnglish
Article number6153150
Pages (from-to)98-107
Number of pages10
JournalIEEE Signal Processing Magazine
Volume29
Issue number2
DOIs
Publication statusPublished - 2012 Jan 1

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Tagging
Multimedia
Spam
Modeling
Social Networks
Annotation
Retrieval
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All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

Cite this

Ivanov, Ivan ; Vajda, Peter ; Lee, Jong-Seok ; Ebrahimi, Touradj. / In tags we trust : Trust modeling in social tagging of multimedia content. In: IEEE Signal Processing Magazine. 2012 ; Vol. 29, No. 2. pp. 98-107.
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In tags we trust : Trust modeling in social tagging of multimedia content. / Ivanov, Ivan; Vajda, Peter; Lee, Jong-Seok; Ebrahimi, Touradj.

In: IEEE Signal Processing Magazine, Vol. 29, No. 2, 6153150, 01.01.2012, p. 98-107.

Research output: Contribution to journalReview article

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