Products are extensively purchased from e-commerce website nowadays by consumers. Users review the product and submit it but these reviews are in bulk so it makes it difficult for the consumer who is willing to buy the product to decide whether to buy or not. A technique which extracts the product features from the huge review corpus is needed to bring forth this problem. To make a good purchase decision it is important to extract best opinion features. Features are going to be extracted from the online reviews. In this paper we proposed a novel approach to extract the best opinion features. Intrinsic, Extrinsic Domain Relevance & feature clustering is used to extract best opinion features. Proposed system performance is evaluated by testing the system inputting different datasets.

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Intrinsic Domain Relevance Extrinsic Domain Relevance Opinion Feature Natural Language Processing Opinion Mining