Design and development of an intelligent web application for direct consumer to consumer trading over Internet

The sudden change in information technology has provided facility of trading in the Internet. There are several platforms available for trading but there is no suitable platform available for direct consumer-to-consumer trading mainly for students studying in a university so that they are able to purchase, sell their goods and make use of various services within the university. So this helps students by providing the facility of easy exchange within a small social network. The mostly used websites for example Snapdeal, Ebay, Flipcart are very global hence does not facilitate the trade and exchange of goods directly among the customers in a small community like campus environment. In this project an innovative approach is used by performing sequence of steps which are recording user profile, performing content and collaborative filtering, and user transactions and applies association rule mining on the buying transactions. Finally the intersection is performed between association manning results and collaborating mining results which provides the recommendations for the customer.