The merge/purge problem for large databases
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Text Classification from Labeled and Unlabeled Documents using EM
Machine Learning - Special issue on information retrieval
Dangerous Decisions: Problem Solving in Tomorrow's World
Dangerous Decisions: Problem Solving in Tomorrow's World
A Distance-Based Approach to Entity Reconciliation in Heterogeneous Databases
IEEE Transactions on Knowledge and Data Engineering
Data association methods with applications to law enforcement
Decision Support Systems
Learning Probabilistic Relational Models
SARA '02 Proceedings of the 4th International Symposium on Abstraction, Reformulation, and Approximation
Learning probabilistic models of link structure
The Journal of Machine Learning Research
Automatically detecting deceptive criminal identities
Communications of the ACM - Homeland security
A hierarchical graphical model for record linkage
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Joint deduplication of multiple record types in relational data
Proceedings of the 14th ACM international conference on Information and knowledge management
Adaptive Name Matching in Information Integration
IEEE Intelligent Systems
Identity resolution: 23 years of practical experience and observations at scale
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Duplicate Record Detection: A Survey
IEEE Transactions on Knowledge and Data Engineering
Eliminating fuzzy duplicates in data warehouses
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Swoosh: a generic approach to entity resolution
The VLDB Journal — The International Journal on Very Large Data Bases
A multi-layer Naïve bayes model for approximate identity matching
ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
Automatically detecting criminal identity deception: an adaptive detection algorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Introduction to special issue on terrorism informatics
Information Systems Frontiers
Semantic similarity measurement using historical google search patterns
Information Systems Frontiers
Journal of Information Science
| Hi-index | 0.00 |
Identity verification is essential in our mission to identify potential terrorists and criminals. It is not a trivial task because terrorists reportedly assume multiple identities using either fraudulent or legitimate means. A national identification card and biometrics technologies have been proposed as solutions to the identity problem. However, several studies show their inability to tackle the complex problem. We aim to develop data mining alternatives that can match identities referring to the same individual. Existing identity matching techniques based on data mining primarily rely on personal identity features. In this research, we propose a new identity matching technique that considers both personal identity features and social identity features. We define two groups of social identity features including social activities and social relations. The proposed technique is built upon a probabilistic relational model that utilizes a relational database structure to extract social identity 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 decisions.