E Commerce Product Rating Based On Customer Review Mining
Many users purchase products through E-commerce websites. Because of online shopping, E-commerce enterprises were unable to trace customer satisfaction for the services provided by the firm. This gave rise to an idea of a system where various customers give reviews about the product and online shopping services, which in turn help the E-commerce enterprises and manufacturers to get customer opinion to improve service and merchandise through mining customer reviews. System uses an algorithm to track and manage customer reviews, through mining topics and sentiment orientation from online customer reviews. In this system user will view and purchase products online. In addition, the Customer will give a review about the merchandise and online shopping services. Certain keywords mentioned in the customer review will be mined and matched with the keywords, which already exist in the database. Based on the comparison, system will rate the product and services provided by the enterprise. This system will use text-mining algorithm in order to mine keywords. The System will allow the reviews of various users and will specify whether the products and services provided by the E-commerce enterprise in terms of good, bad, or worst. We use a database of sentiment based keywords along with positivity or negativity weight in database and then based on these sentiment keywords mined in user review is ranked.
|IEEE Paper Year||2015|