Feature-Based Opinion Mining Using Ontological Resources

Abstract

One of the important types of information on the Web is the opinions expressed in the user generated content, e.g., customer reviews of products, forum posts, and blogs. Customer reviews of products are focused in this paper. Mining opinion data that reside in web is a way to track opinions of people on specific product. Opinion mining is a recent subdiscipline of computational linguistics which is concerned not with the topic a document is about, but with the opinion it expresses. To aid the extraction of opinions from text, recent work has tackled the issue of determining the orientation of subjective terms contained in text, i.e. deciding whether a term that carries opinionated content has a positive or a negative connotation. In this paper the task of deciding whether a given term has a positive connotation, or a negative connotation by using feature-based opinion mining with ontology where opinions expressed towards each feature of an object or a product are extracted and summarized. In this context, the goal is to study the role of domain ontology to structure and extract object features as well as to produce a comprehensive summary.