A Survey : Ontology Based Information Retrieval For Sentiment Analysis

The rapidly growing data on the web has created a big challenge for directing the user to the web pages in their areas of interest. Sentiment analysis or Opinion mining plays an important role in finding the area of interest based on user’s previous actions. Social networking portals have been widely used for expressing opinions in the public domain. Text based sentiment classifiers often prove inefficient. Semantic web is the solution for Searching relevant information from huge repository of unstructured web data. Semantic web leads the idea of ontology as background knowledge represents the concepts and the relationship in specialized domain. The basic idea behind this survey is to take domain ontology for providing more elaborate sentiment scores. We discuss an approach where information retrieved from web and ontology is created before sentiment classification and focuses on how to classify the semantic orientation of text.