AN AGENT BASED FRAMEWORK FOR SENTIMENT CLASSIFICATION OF ONLINE REVIEWS USING ONTOLOGY

In this study, we design and develop an agent based framework for sentiment classification of online reviews using ontology. The book review ranking is based on the sentiment classification result. We propose a novel approach with the help of the JADE platform to solve problems by non-visual automatic sentiment classification. The description of book reviews ranking are generated from the ontology based mapping. This approach employs the data extraction agent which is used to retrieve the books comments i.e., the user reviews from the specified blogs. The Second agent is the recommendation agent i.e., domain ontology is used for identifying domain related features in comments. The Third agent is feature selection agent in which XML document content is split into single sentence. Each word in the sentence is mapped with ontology. A Mapping process is used for identifying the domain related sentences in that context. These processes are used for ranking the book results based on customer reviews. The book review ranking system can be extended to other product-review easily.