Combining random sub space algorithm and support vector machines classifier for Arabic Opinions Analysis

Abstract

In this paper, an Arabic Opinion Analysis system is proposed. These sorts of applications produce data with a large number of features, while the number of samples is limited. The large number of features compared to the number of samples causes over-training when proper measures are not taken. In order to overcome this problem, we introduce a new approach based on Random sub space (RSS) algorithm integrating Support vector machine (SVM) learner as individual classifiers to offer an operational system able to identify opinions presented in reader’s comments found in Arabic newspapers blogs. The main steps of this study is based primarily on corpus construction, Statistical features extraction and then classifying opinion by the hybrid approach RSS-SVM. Experiments results based on 800 comments collected from Algerian newspapers are very encouraging; however, an automatic natural language processing must be added to enhance primitives’ vector.