Business English Learning Path Based on Knowledge Mapping in the Context of Educational Informatisation

Abstract

In this paper, we first construct ontology and entity learning to construct a knowledge graph by matching the knowledge to the schema layer. Then, we obtain users’ learning styles, extract interest keywords from user behavioral data, map them into the vector space encoded based on the KgTransH algorithm, and compare them with the original algorithm on multiple datasets. Then, the business English learning path is planned based on learning path length, learning time and achievement ranking. Finally, the effect of the knowledge graph-based business English learning path planning method is analyzed through comparative experiments. Through 50 iterations, the satisfaction of the knowledge graph method, GA method and ACO method are between 4.3-4.8, 4-4.7 and 4.05-4.7, respectively, which indicates that the method of this paper is better than the other methods. This study is important for improving the learning effect of Business English.

Keywords

• knowledge graph
• ontology construction
• user profiling
• path planning
• business english
• 97d60