Research And Implementation Of E-commerce Recommendation And Visualization System Based On Rough Set

With the proliferation of computers and the development of the Internet, E-commerce gradually on the rise and occupy a larger proportion of retail in today's society. Various studies in the ascendant around the E-Commerce. Recommendation system is one of the important research direction, this for the development of electronic commerce has great practical significance.At present, almost all large e-commerce website, Such asAmazon.com, eBay, dangdang, amazon.cn,360buy, etc. Those website are use of various forms of recommender System in different levels. But today's research is focused on a variety of recommended techniques, there is not much research about the visualization of e-commerce system.At first, This paper examined the status of e-commerce sites recommended techniques, Compared the current technology of e-commerce recommended techniques. Propose a mechanism about tendency of user to buy based on rough set. Research and design recommendation algorithms. Design the algorithm between the user behavior and buying preferences by reduced the data of user's behavior.Second, This paper analyzed and tested the mainstream e-commerce site based usability testing technology. Get the current site recommended visualization system shortcomings, and designed a new E-commerce recommendation system. And soon we tested the new system, and verified the new system.The paper has done a lot of usability testing, get many of the recommendations and methods form users for designing the new system. We know the new system is more remarkable by the usability testing. But Algorithm validation studies not carried out too much on the paper. This is the follow-up to the need for improved working.