Word association norms, mutual information, and lexicography
Computational Linguistics
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Efficient Adaptive-Support Association Rule Mining for Recommender Systems
Data Mining and Knowledge Discovery
Data association methods with applications to law enforcement
Decision Support Systems
DBMS Research at a Crossroads: The Vienna Update
VLDB '93 Proceedings of the 19th International Conference on Very Large Data Bases
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining Market Basket Data Using Share Measures and Characterized Itemsets
PAKDD '98 Proceedings of the Second Pacific-Asia Conference on Research and Development in Knowledge Discovery and Data Mining
Proceedings of the 2004 ACM symposium on Applied computing
Noun classification from predicate-argument structures
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
Fast Binary Feature Selection with Conditional Mutual Information
The Journal of Machine Learning Research
Aligning database columns using mutual information
dg.o '05 Proceedings of the 2005 national conference on Digital government research
A Mathematical Theory of Communication
A Mathematical Theory of Communication
Data mining approaches for intrusion detection
SSYM'98 Proceedings of the 7th conference on USENIX Security Symposium - Volume 7
Parsing a natural language using mutual information statistics
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 2
Using mutual information for selecting features in supervised neural net learning
IEEE Transactions on Neural Networks
Evaluating ontology mapping techniques: An experiment in public safety information sharing
Decision Support Systems
Decision support for determining veracity via linguistic-based cues
Decision Support Systems
Topological analysis of criminal activity networks: enhancing transportation security
IEEE Transactions on Intelligent Transportation Systems
An intelligent decision-support model using FSOM and rule extraction for crime prevention
Expert Systems with Applications: An International Journal
PutMode: prediction of uncertain trajectories in moving objects databases
Applied Intelligence
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In recent years border safety has been identified as a critical part of homeland security. The Department of Homeland Security searches vehicles entering the country for drugs and other contraband. Customs and Border Protection (CBP) agents believe that such vehicles operate in groups and if the criminal links of one vehicle are known then their border crossing patterns can be used to identify other partner vehicles. We perform this association analysis by using mutual information (MI) to identify pairs of vehicles that may be involved in criminal activity. CBP agents also suggest that criminal vehicles may cross at certain times or ports to try and evade inspection. We propose to modify the MI formulation to include these heuristics by using law enforcement data from border-area jurisdictions. Statistical tests and selected cases judged by domain experts show that modified MI performs significantly better than classical MI in identifying potentially criminal vehicles.