Profile Categorization System based on Features Reduction
نویسندگان
چکیده
Though the enormous impact of social media on our daily life, we observe a lack of information about those who create the contents. In this regard, author profiling tries to determine the profile category of authors by analysing their published texts. This paper presents a profile categorization system to solve the multi-class categorization problem. The system consists of two modules: the processing module and the classifying module. In the first module TF-IDF with threshold filtering method are used to extract the relevant terms. While support vector machine (SVM) is used in the classifying module. Our proposed feature reduction method is tested using the RepLab 2014 Data set and evaluated using performance measures: precision, recall and F-measure. Result obtained show that proposed method improves system performance when solving a multi-class profile categorization problem.
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