Semantic Web-Based Personalized Recommendation System of Courses Knowledge Research
According to personalized service in teaching system, this paper proposes curriculum resources personalized recommendation algorithm based on semantic web technology. First, we get a collection of curriculum resources of interests in terms of the user evaluation and user browsing behavior, and then based on the relationship between the concept in the domain ontology, calculate semantic similarity between core concepts of different user evaluation, and finally according to the similarity decide the similarity of user preferences interests, find the nearest neighbors with similar interests, in order to achieve learning resources personalized recommendations. Combination of ontology model of “compile theory “course knowledge, we design and implement personalized learning recommendation system.