With the development of e-commerce, shopping online is becoming more popular. The convenience of new web technologies enables us to freely express our opinions and reviews for various products purchased online. Therefore, consumer reviews, opinions and shared experiences in the use of the product is a powerful source of information about consumer preferences that can be used in recommending products based on the reviews. Despite the importance and value of such information, there is no comprehensive mechanism that formalizes the opinions by selecting and retrieving the opinions and then displaying the key strengths and weaknesses of a product. In this project, we propose a system where the product reviews from e-commerce platforms are taken into consideration and are then analyzed and topic mining is performed on these customer reviews. The reviews are then categorized into positive and negative for a product which helps the manufacturer and the seller. There might be a few aspects of a product where the feature might be good and the same can be said for the negative aspects as well. Hence, topic mining helps in categorizing a product into a positive and a negative one which helps the manufacturer to understand the key strengths of a specific product and in turn helps the e-commerce platform to understand popular products that can be hosted on the website. This categorization of negative and positive reviews for a product makes it easy for a buyer to narrow down their choices while browsing for a product from a specific seller.
