Semantic Web Recommendation Model of Distributing Educational Resource

According to the requirements of the educational resource distributing features and semantic-based searching, this paper presents a semantic recommendation model of educational resource using publish/subscribe technologies. The resource way to message is published to the distributing model system; the users´ personalized requests are stored in local as subscribe ways. The system gives an approach to realize the information services change from users searching information to server pushing personalized content, which implements information matching content-based. The model system is significantly more efficient deployed than other existing searching educational resource based on Web page. Experiment results show that the distributing model system gives better performance than traditional Web page recommendation methods in the traditional Web.