Personalized Knowledge Push Service Based on Semantic Web

The traditional knowledge push service based on non-semantic is inefficient in the hit ratio and accuracy because of the lack of semantic description and modeling to user preferences and knowledge resources. Semantic Web has unique advantages such as the robotization of the meaning interpretation, the decentralization of knowledge expression and the information identification by ontology. It provides a perfect technology for knowledge push service in the manner and level of services. Inspired by the relevant technologies of semantic web and proceed from users´ actual demands, a three layers structure intelligent knowledge push services framework model is proposed. The architecture of the model is discussed. The knowledge push service based on user preference optimizes the current knowledge service course and enhances the value of the knowledge services in the semantic web environment.