An Efficient Semantic Retrieval Method for Network Education Information Resources

To improve the performance of network education information resources system, this paper proposes ontology-based similarity algorithm and semantic query expansion method. We mainly study ontology reasoning and define reasoning rules based on knowledge point ontology. Combining with various conceptual relationships in knowledge point ontology, we define corresponding rules and verify them by experiments, which lays a foundation for semantic extension. Then, a domain ontology-based information retrieval model is proposed based on the above content. By separating the relationship between concepts, the semantic similarity and correlation are calculated by using the conceptual hierarchy and association relationship and considering various factors, the semantic similarity and correlation are synthetically quantified into the semantic association degree for semantic retrieval. Finally, the prototype system of semantic retrieval is designed and validated, and the simple retrieval of resources is realized.