Making large-scale support vector machine learning practical
Advances in kernel methods
A hierarchical approach to wrapper induction
Proceedings of the third annual conference on Autonomous Agents
Natural Language Processing with Python
Natural Language Processing with Python
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Sex trafficking is the process and means of using force, fraud, or coercion to obtain and compel men, women and children into commercial sexual exploitation. Prevalent in both international and domestic spheres, this form of human trafficking constitutes a serious crime. Traffickers use a variety of means to advertise the illicit sexual services of the children and women they offer, including Internet classified ads, bulletin boards, and social media associated with escort and massage services (EMS). Clients ("johns") of the EMS fronts for prostitution also use the Internet and social media to compare their experiences and offer leads to one another. Law enforcement organizations have implemented a number of initiatives to combat child sexual trafficking. We describe a prototype law enforcement support system developed to automatically compile and correlate information from open Internet sources about trafficking and sexual abuse of women and especially children. The system, called TrafficBot, employs information retrieval, information integration, and natural language technologies to build a data warehouse allowing various visualizations of information for the benefit of law enforcement. We discuss the current capabilities of TrafficBot, how it could be used by law enforcement, and suggest some future directions.