Combining Predation Heuristics and Chat-Like Features in Sexual Predator Identification
نویسندگان
چکیده
In this paper we present a system for sexual predator detection which combines two different approaches: a knowledge-based system that makes use of pattern matching according to hand-coded patterns that represent typical predator behaviors, and a learning-based system which employs surface linguistic features like capitalization and chat-like expressions. These approaches are combined in a chained fashion, being the learner applied to the suspicious predators as reported by the knowledge-based system. While the results of the system evaluation on the training collection are nice, the test run results for the official Sexual Predator Identification sub-task have shown much room for improvement.
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