Design and implementation of personalized recommendation system for user
Hou Le-cai · Jisuanji gongcheng yu sheji · 2009
In order to implement personalized services, understanding user interest becomes the critical mission for providing services. So an information method for hidden collection of browsing content, browsing time span and operation time span is proposed. The key elements are extracted through cleaning the content of web page which crawled by web crawling program. Then the document model is built via VSM and the recommended library is built by using class method of SVM. The model is built to recommend information to user based on user interest information collected from client and the similarity between this model and recommended library. In addition, implementing of the recommendation system is introduced. The precision ratio is used to evaluate this system, and it’s experimental results show that our system has good at recommending information to users according to their interests.