Design And Implementation Of Online Mall Recommendation System Based On Mapreduce

With the developing of internet technology, more and more people dependent onaccess to information by the internet. In the era of information explosion, because of arise in the amount of information, how to find out useful information from massivedata become a hot research topic. Recommended system provides informationfiltering technology, which can help users to save time in the face of large amounts ofinformation, and it can improve customer satisfaction effectively, this paperproposes a personalized recommendation system.Personalized recommendation technology recommend information to userswhich they may be interested in based on their interest or preference, so it can providepersonalized service according to different users. Personalized recommendationtechnology broad range of applications, such as e-commerce, e-commerce sites canincrease purchase through personalized recommendation system. Personalizedrecommendation system technology is essentially an information filtering technology,it is an integrated system with a fusion of a variety of data mining algorithmscombined with user-related information, to predict to interest or potential interest ofusers. Recommended system is divided into different types depending on therecommendation algorithm. In the traditional recommendation system classification,it is divided into content-based systems, collaborative filtering system, hybridsystem. Because of the different algorithms are used in different conditions, therecommend effect is not the same one though the recommendation algorithm are usedsame information.Generally, in the practical application of recommendation systems,it tend to hybrid recommendation system, which is a method of mixing variousrecommendation algorithm, it can improve the recommendation result effectively. The content of paper is to research how to help a user to access the interestedinformation automatically in the mass commodity product information data, whichcan avoid interference. Firstly, this paper introduces the research background andresearch status, then it gives the main work of this paper. Secondly, part of the articleto be achieved, we use the appropriate technology to ensure the conduct of systemdevelopment smoothly. After positioning requirements analysis and systems, it isproposed to improve the algorithm on the basis of the traditional algorithm, the papershows the final results by the system interface after the introduction of the databasedesign and form design. The main work of this paper contains a study of personalizedrecommendation system algorithm, combined with practical application requirements,it is designed to provide users with an effective personalized recommendationsmanagement system through a combination of research results and needs analysis,now the system is realized.