Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
COPLINK: managing law enforcement data and knowledge
Communications of the ACM
Locating hidden groups in communication networks using hidden Markov models
ISI'03 Proceedings of the 1st NSF/NIJ conference on Intelligence and security informatics
Untangling criminal networks: a case study
ISI'03 Proceedings of the 1st NSF/NIJ conference on Intelligence and security informatics
COPLINK agent: an architecture for information monitoring and sharing in law enforcement
ISI'03 Proceedings of the 1st NSF/NIJ conference on Intelligence and security informatics
CrimeWalker: a recommendation model for suspect investigation
Proceedings of the fifth ACM conference on Recommender systems
A link analysis model based on online social networks
WISM'11 Proceedings of the 2011 international conference on Web information systems and mining - Volume Part II
Community detection based on a semantic network
Knowledge-Based Systems
A novel measure of edge centrality in social networks
Knowledge-Based Systems
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When a criminal probabilistic network has been constructed, criminal investigators can access verified information about some nodes of network after investigations. Effective and efficient techniques are needed to help law enforcement and intelligence agencies to infer the state of other nodes and choose the next new investigative objects in the criminal network. In this paper, we propose a technique that employs a belief propagation algorithm to help criminal investigators to infer the criminal probability of other members by using verified partial information. In an updated criminal probabilistic network, this paper also presents a technique called EMPFS which extends the modified PFS algorithm. EMPFS algorithm is used to solve choice of next key investigative objects from criminal network. Experimental results show that the precision and efficiency of two techniques might be improved by exact constructing of the crime probabilistic network.