Collocating Recommendation Method for E-Commerce Based on Fuzzy C-Means Clustering Algorithm

In order to reduce the time for customers select commodities they are interested in, improve purchase efficiency, success rate of sales merchants, and create greater economic benefits enterprises this project collects information data e-commerce users, using neural network model analyze mine characteristics shopping records users. According analysis results, a user commodity recommendation system based on is implemented by mining technology. Through combination database technology, transaction browsing generated in process transactions collected. The collected preformatted used as input mining. Then, it uses technology that users makes matching according types commodities, recommends under given scene established prediction model. By combining fuzzy clustering with collaborative filtering algorithm, paper products which mined from historical information.