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 language | English (US) |
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Pages | 150-155 |
Number of pages | 6 |
DOIs | |
State | Published - 2008 |
Event | IEEE International Conference on Intelligence and Security Informatics, 2008, IEEE ISI 2008 - Taipei, Taiwan, Province of China Duration: Jun 17 2008 → Jun 20 2008 |
Other
Other | IEEE International Conference on Intelligence and Security Informatics, 2008, IEEE ISI 2008 |
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Country/Territory | Taiwan, Province of China |
City | Taipei |
Period | 6/17/08 → 6/20/08 |
Keywords
- Identity matching
- PRM
- Probabilistic models
- Social context
ASJC Scopus subject areas
- Artificial Intelligence
- Information Systems