Foreign Language Teaching Resources Recommendation Approach Based on Knowledge Map

Abstract

To improve the utilization of foreign language online teaching resources, a resource recommendation model based on knowledge map is proposed. The scheme constructs the ontology of knowledge map in Python by analyzing the data of online users’ learning behaviors. Then Neo4j is adopted to store the map database of agricultural knowledge map. In the process of resource recommendation, a new kind of knowledge map representation learning algorithm is introduced into collaborative filtering algorithm to extract structured information in the knowledge map. Finally, a foreign language teaching resource recommendation system based on knowledge map is designed and implemented through an example. Through comparative experimental analysis, it is proved that the method is superior to the traditional recommendation method in terms of accuracy index and it can improve the satisfaction of teachers and students with different demand for foreign language studying.