Bengali text classification using SVM

Abstract

In current scenario, lot of online news is available for different topics on Internet from which textual data is increasing rapidly. Due to this, text classification becomes essential to organize them properly so that important news can be searched easily as well as to avoid data loss. One effective solution for this problem is to classify the news into different classes or to extract most important and useful information. With the rapid growth of Text sentiment analysis, the demand for automatic classification of electronic documents has increased by leaps and bound. The paradigm of text classification or text mining has been the subject of many research works in recent time. In this paper we propose techniques for Bengali text classification. In one method we take all the words from document and in another method we extract keywords from each document. We found the Support vector machine (SVM) is the most appropriate to work with our proposed model. The achieved results show significant increase in accuracy compared to earlier methods.