Websites for E-shopping is becoming more accepted nowadays. Companies are eager to know about their buyer buying behaviour to expand their item sale. Extracting knowledge from a large database, Data Mining is the key approach to use for an accurate result. But in our context, we have to process customer reviews from large E-commerce, a database for which Opinion Mining is the best approach for mining buyer reviews about the item set. The widely accessible internet resources are letting the users shop any products anywhere, anytime at any cost. In existing papers, opinion mining is used to process the online product reviews, feature and suggest the top product among others. Natural Language Processing (NLP), modified SVM is used to determine the polarity of reviews. In this paper, a novel approach is proposed for opinion mining of item reviews. The objective is to encourage the buyers and assist them in choosing the right product. It is based on natural language processing, opinion mining and modified SVM. Results indicate that the proposed methods are highly effective and efficient in performing their tasks. We will also aim at developing the accuracy of our opinion polarity detection and feature extraction among other techniques.
Volume 11 | 03-Special Issue
Pages: 1829-1837