PRM-based identity matching using social context

Jiexun Li, G. Alan Wang, Hsinchun Chen

Research output: Contribution to conferencePaperpeer-review

Abstract

Identity management is critical for many intelligence and security applications. Identity information is not reliable due to the problems of unintentional errors and intentional deception by the criminals. Most of existing identity matching techniques consider personal identity features only. In this article we propose a PRM-based identity matching technique that takes both personal identity features and social contexts into account. We identify two groups of social context features, namely social activity and social relation features. Experiments show that the social activity features significantly improve the matching performance while the social relation features effectively reduce false positive and false negative.

Original languageEnglish (US)
Pages150-155
Number of pages6
DOIs
StatePublished - Sep 22 2008
Externally publishedYes
EventIEEE International Conference on Intelligence and Security Informatics, 2008, IEEE ISI 2008 - Taipei, Taiwan, Province of China
Duration: Jun 17 2008Jun 20 2008

Conference

ConferenceIEEE International Conference on Intelligence and Security Informatics, 2008, IEEE ISI 2008
CountryTaiwan, Province of China
CityTaipei
Period6/17/086/20/08

Keywords

  • Identity matching
  • PRM
  • Probabilistic models
  • Social context

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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