Research On Ontology-based Personalized Semantic Retrieval Of Educational Resources

With the rapid development of digitization of educational resources, digital educational resources exhibit rapid growth. User can find educational resources through information retrieval. However, traditional search engines are mostly generic retrieval technology based on text and keywords, which hampers them from satisfying the demand of personalized and creative learning.This paper studies the personalized, ontology-based semantic retrieval technology of educational resources. The personalized, ontology-based semantic retrieval technology of educational resources creates semantic repository of educational resources using ontological technologies and constructs personalized user interest model based on the user’s characteristics. According to the user interest model, the semantic retrieval system can provide personalized information to the user from semantic repository. That will satisfy the individual requirements of different users and improve the relevance and the effectiveness of the retrieval.This paper firstly introduces the basis of ontology and semantic web. It probes the description of educational resources ontology according to the seven steps of the semantic support of ontology in OWL. Then, this paper construct a user interest model, which includes collection of user behavior, extraction of user interest, and update of user interest database and user interest ontology library. And similarity algorithm of semantic retrieval is studied, including concept similarity and attributes similarity, and some models of semantic similarity calculation were analyzed and compared. Finally, the design of ontology-based personalized semantic retrieval prototype system of educational resources is described. The prototype system consists of three modules:user interest module, the educational resource semantic module and retrieval processing module.This paper discusses feasible schemes on ontology-based acquire of educational resources, semantic retrieval, user interest model construction and personalized semantic retrieval of educational resources, which exemplifies it as a practical guidance.