ACM SIGIR Forum
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Email mining toolkit supporting law enforcement forensic analyses
dg.o '05 Proceedings of the 2005 national conference on Digital government research
Automated criminal link analysis based on domain knowledge: Research Articles
Journal of the American Society for Information Science and Technology
Toward Spotting the Pedophile Telling victim from predator in text chats
ICSC '07 Proceedings of the International Conference on Semantic Computing
Chat mining: Predicting user and message attributes in computer-mediated communication
Information Processing and Management: an International Journal
Analyzing the terrorist social networks with visualization tools
ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
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Cyber criminals exploit opportunities for anonymity and masquerade in web-based communication to conduct illegal activities such as phishing, spamming, cyber predation, cyber threatening, blackmail, and drug trafficking. One way to fight cyber crime is to collect digital evidence from online documents and to prosecute cyber criminals in the court of law. In this paper, we propose a unified framework using data mining and natural language processing techniques to analyze online messages for the purpose of crime investigation. Our framework takes the chat log from a confiscated computer as input, extracts the social networks from the log, summarizes chat conversations into topics, identifies the information relevant to crime investigation, and visualizes the knowledge for an investigator. To ensure that the implemented framework meets the needs of law enforcement officers in real-life investigation, we closely collaborate with the cyber crime unit of a law enforcement agency in Canada. Both the feedback from the law enforcement officers and experimental results suggest that the proposed chat log mining framework is effective for crime investigation.