Design And Implementation Of E-Shop Based On Recommend Algorithm

With the development of society and economy, the living standards of the people improved steadily and the Internet, mobile Internet industry, the rapid development, now has been accustomed to the network to handle all sorts of things, such as Webpage browse, purchase, learning and work etc.. But as the number of users and products to grow geometrically amazing speed, internet life has brought great convenience to people at the same time, it also brings a lot of inconvenience to people’s life. Of every hue useful, full of spam users view, at the same time, the development of e-commerce has brought more and more challenges. As the user can quickly obtain the necessary information from large amount of data, the personalized recommendation system of e-commerce emerges.Personalized recommendation system of e-commerce is based on user preferences and purchase log data, recommendation and information of interest to the user. But with the development of e-commerce, the number and types of merchandise to multiply, customers often need to spend considerable time to find their own love or want goods. The user will be submerged in the information overload problem, a considerable part of the user will be gradually lost in the browser that a large number of redundant information and products. In orde. In order to solve these problems, a personalized recommendation system emerge as the times require.Personalized recommendation system is based on an advanced business intelligence platform and mass data, help the electronic commerce website provides a completely personalized decision support and information service for the customer information system. Recommendation system of shopping website recommendation for the user, and can automatically complete the process to choose goods personalized, personalized to meet the demand, user based recommendation: website sells goods, the city in the past, the customer purchasing behavior and records, used to speculate the future might purchase behavior of customers.In the age of electronic commerce, the business through the shopping website provides a wealth of goods for the user, the user login the website to obtain a large number of goods, but not through the screen at a glance to understand all of the goods, not in a large number of goods directly to find the one you love. So, the customer needs a system of online shopping, can according to the customer’s own interest hobby recommend customers like or may be interested in, this is the research target to achieve in this paper.Based on the above requirement, the main work and research results are as follows: ASP.NET design and development of online shopping system based on.Combined with various recommendation algorithms and buy the browse information data, the mining of the hidden information, quickly and accurately infer the user needed goods.Through the above research work, this paper design and implement a system of online shopping recommendation algorithm based on the development of language to C#language, combining the evaluation results of the recommendation algorithm, compared with the current system of online shopping mall, recommendation algorithm used in this paper is to compare the accuracy and reliable, to validate the system recommended, to meet user the demand for personalized recommendation.