The Designation And Implementation Of Rest Based Personalized Data Service

Recommendation System is performing very important role in the Internet these days and has a very good prospect. Base on recommendation system, personalize data from personalize data service is also very important to E-commerce system. Nowadays, Internet web sites, which provide passive information services, can no longer satisfy the users’needs, which increase gradually. Personalize data service comes into a being in a wave of e-commerce development and becomes one of the research focuses in the Internet industry.Compared with the traditional passive information service, personalize data service can provide more efficient service than ever. It pushes information to different user according to the user browsing history, buy history and comment history. In general, recommendation system contains three modules, the user data-collecting module, user data module analyzing module and user data analyzing module. The user data-collecting module is responsible for collecting user data from application system, such as Weibo and Taobao. The user module-analyzing module is responsible for extracting data from user history and storing these data in database or other structured data storage method. User data-analyzing module is responsible for analyzing the structured user data, find the implicit relationship between users and users’ interest. Recommendation system will use the analyzing results from user data-analyzing module and give user different recommendations. At the same time, with the Mobile Internet growing rapidly, a lot of open service platform emergence, for example Weibo Open Platform and Taobao Open Platform which is known for TOP These open platforms provide the third-party application with a lot of resources and services. So the third-party applications are also growing rapidly as open platforms. The third-party applications also bring new flow and new opportunities to the existing open platforms. So the open platforms resolve the resource-sharing problem with different systems and are the foundation of a lot of third-party applications.This paper designs a Personalized Data Service and one data service open platform, which provides REST APIs. And this paper also implements a reader Personalized data service for BUPT library. This service can find the implicit relationships between by analyzing user borrowing-data from BUPT library.