Design And Implementation Of Hybrid Recommendation System Rblog Based On User Preferences

With the development of Internet technology and the intelligent service, make it quickly popular in people. People can get all kinds of information through it. Such as, people can obtain much information by search engine. At the same time, people enjoy the convenience provided by Internet, they have a happiness trouble. How quickly find the valuable information in the mass of information? Scholar comes up with the recommendation technology. The recommendation system is the application of the technology. Firstly, it produces a recommendation list by the user interests. Finally, it will provide the list to the user. Thus, the users don’t need to waste a lot of time and effort for finding the useful information in the mass of information. At present, many the domestic e-commerce sites have applied the technology in the site, such as Dangdang, Jingdong Mail, Taobao.This paper introduces the development and application of the recommendation system, and the problems in practice. Thus, from the aspect of the concept, classifications and technology describe the recommendation system, especially analysis the content-based and collaborative-based recommendation system in detail.This paper builds an enterprise development platform. The system architecture of MVC is achieved by the currently popular J2EE technologies, such as Struts, Spring and Hibernate technology. The function of a hybrid recommendation system based on user preferences Rblog is analysis in detail. Give a detail design project of the browser side, the server side and the database side. Finally, it achieves the hybrid recommendation system model based on user preferences Rblog on this basic.In this paper, the content-based recommendation algorithm, the user-based collaboration and the item-based collaboration are combined to implement the hybrid recommendation system based on user preference Rblog.It nicely combines the advantages of the three recommendation algorithms.In addition, the paper provides a full-text search engine. It implements by using Lucene API.