Paper Details

Social media is becoming a major and popular technological platform that allows users to express personalopinions toward the subjects with shared interests, opinion are good for decision making to People would want to knowothers' opinion before taking a decision, while corporate would like to monitor pulse of people in a social media abouttheir products and services and take appropriate actions. This paper reviewed about world are realizing that ecommerce is not just buying and selling over Internet, rather it is improve the efficiency to compete with other giants inthe market. Their opinions on specific topic are inevitably dependent on many social effects such as user preference ontopics, peer influence, user profile information. E-Commerce sites are gaining popularity across the world. People visitthem not just to shop products but also to know the opinion of other buyers and users of products. Online customerreviews are helping consumers to decide which products to buy and also companies to understand the buying behavior ofconsumers. In this paper we have created a prototype web based system for recommending and comparing products soldonline. We have used natural language processing to automatically read reviews and used Naive Bayes classification todetermine the polarity of reviews. We have also extracted the reviews of product features and the polarity of thosefeatures. We graphically present to the customer, the better of two products based on various criteria including the starratings, date of review, the helpfulness score of the review and the polarity of reviews.

Prof. Rahul Kadam, Vinayak Gargote, Chetan Lokhande, Prashant Wankhade, Srushti Mahabole, “Product Recommendation System using Opinion Mining”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 1, pp. 350-353, January 2017.