Ontology-Based Arabic Documents Classification

  • Mohammed M. Abu Jasser -----> Dr. Rebhi S. Baraka

 Automatic documents classification is an important task due to the rapid growth of the number of electronic documents. Classification aims to assign the document to a predefined category automatically based on its contents. In general, text classification plays an important role in information extraction and summarization, text retrieval, question answering, e-mail spam detection, web page content filtering, and automatic message routing.
Most existing methods and techniques in the field of documents classification are keyword based without many features. Even methods that ontology-based classification is limited to English language support.
In this research, we propose an approach to investigate the role of ontology (an Arabic news domain ontology) in Arabic documents classification. The results show that the proposed ontology-based approach achieves improvement in the process of documents classification based on the different evaluation criteria. The experimental results show that the accuracy of the approach is 92%. These results prove that the ontology contribute effectively in the process of Arabic documents classification. 
Keywords: Arabic Language, Text Mining, Documents Classification, Documents Annotation, Ontology, News Ontology.