Deep analysis of knowledge in one´s writings

Reading the opinion behind the text is a big challenge. In another way, we need to automatically read opinions and moods as a natural language. Ontology -based plays a main role to solve the problems in this field. That is from the features of the ontology based as covering the semantics of the concepts. So, in this paper, we propose a flexible classification opinion mining tool. This proposed method based on ontology- based. The proposed method uses NLTK (Natural Language Processing Toolkit) with Python as a useful knowledge to get more representative word occurrences in the corpus. Also, we not only use a WordNet and SentiWordNet ontologies to assign the word as POS (part of speech), but we also create a specific purpose ontology by OWL editor as Protégé. Then we create a more general opinion mining tool where the specific purpose ontology file was selected to use for classification the text. We apply our proposed method on lists of long texts for different writers, and then we can classify these writers depending on their writings.