Arabic Text Classification Using Maximum Entropy

Abstract

In organizations, a large amount of information exists in text documents. Therefore, it is important to use text mining to discover knowledge from these unstructured data. Automatic text classification considered as one of important applications in text mining. It is the process of assigning a text document to one or more predefined categories based on their content. This paper focus on classifying Arabic text documents. Arabic language is highly inflectional and derivational language which makes text mining a complex task. In our approach, we first preprocessed data using natural language processing techniques such as tokenizing, stemming and part-of-speech. Then, we used maximum entropy method to classify Arabic documents. We experimented our approach using real data, then we compared the results with other existing systems.