Recommendation algorithm design of network learning resource based on ontology

In view of the problem that learners are faced with information overload in the network learning platform, which leads to insufficient access to personalized information, this paper applies the domain ontology construction method to model and represent the data of learning courseware, and constructs a learner feature model based on domain ontology and learner attribute information. The model has semantic support combined with domain ontology theme and basic information elements of learners and updates with time. Based on the learning feature model, a collaborative filtering recommendation method is designed to integrate similarity, which can effectively solve the problem of cold start and lack of semantic support. The experimental results show that the data recommendation precision of proposed method is better than the traditional collaborative filtering recommendation method, the accuracy of data recommendation decreased by 12.29%, effectively improving the quality of data recommendation.