Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Mining chat conversations for sex identification
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
A target oriented agent to collect specific information in a chat medium
ISCIS'06 Proceedings of the 21st international conference on Computer and Information Sciences
Expert Systems with Applications: An International Journal
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Mining textual data in chat mediums is becoming more important because these mediums contain a vast amount of information, which is potentially relevant to a society's current interests, habits, social behaviors, crime tendency and other tendencies. Here, sex identification is taken as a base study in information mining in chat mediums. In order to do this, a simple discrimination function and semantic analysis method are proposed for sex identification in Turkish chat mediums. Then, the proposed sex identification method is compared with the Support Vector Machine (SVM) and Naive Bayes (NB) methods. Finally, results show that the proposed system has achieved accuracy over 90% in sex identification.