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A comparison of textual data mining methods for sex identification in chat conversations
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Internet and chat mediums provide important and quite useful information about human life in different societies such as their current interests, habits, social behaviors and criminal tendency. In this study, we have presented an intelligent identification system that is designed to identify the sex of a person in a Turkish chat medium. To do this task, a target oriented chat agent is implemented. A simple discrimination function is proposed for sex identification. The system also uses a semantic analysis method to determine the sex of the chatters. Here, the sex identification is taken as an example in the information extraction in chat mediums. This proposed identification system employs the agent and acquires data from a chat medium, and then automatically detects the chatter's sex from the information exchanged between the agent and chatter. The system has achieved accuracy about 90% in the sex identification in a real chat medium.