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Knowledge is data that represents the outcome of computer-based cognitive processes such as perception, learning, association, and reasoning, or the translation of knowledge acquired by human [10]. It is the language by which human express their understanding about the concept. The concepts and the instances of a particular domain are expressed in the knowledge base also referred as the semantic knowledge dictionary. It is one of the most important techniques to represent the knowledge for a domain. Domain Ontology is developed to formally define the concepts, relationships, and rules so as to include the semantic content of the domain. The semantic approach uses the concepts in the documents to establish the contextual relationship rather than the terms. Issues like synonymy and polysemy may not be resolved if terms are used as indices while modelling the text documents. Various semantic-based information extraction approaches like Latent Semantic Indexing [11] and Latent Dirichlet Allocation [12, 13] techniques are used for building the relationship among the indexed terms, so as to represent the contexts between the concepts. This chapter focuses on developing domain Ontology to represent the features and their related terms mentioned in the product/service reviews generated in social media web sites.