Conference proceeding
Criminal identity resolution using social behavior and relationship attributes
Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics
Jul 2011
Abstract
We propose a criminal identity resolution technique that utilizes both personal identity and social identity information. Guided by existing identity theories, we examine three types of identity features, namely personal identity attributes, social behavior attributes, and social relationship attributes. We also explore three matching strategies, namely pair-wise comparison, transitive-closure, and collective resolution. Our experiment on synthetic data sets show that both social behavior and relationship attributes improve the performance of identity matching as compared to the use of personal identity attributes alone. The results also show that the collective relational resolution approach outperformed other approaches in terms of F-measure.
Metrics
11 Record Views
3 citations in Scopus
Details
- Title
- Criminal identity resolution using social behavior and relationship attributes
- Creators
- Jiexun Li - Drexel UniversityG. Alan Wang - Virginia TechJingjing Li - Urban Health Collaborative (2015-)
- Publication Details
- Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics
- Conference
- 2011 IEEE International Conference on Intelligence and Security Informatics
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Urban Health Collaborative
- Scopus ID
- 2-s2.0-80052915397
- Other Identifier
- 991019173448304721