| In recent years,with the integration of the Internet and education,as well as the impact of the COVID-19,online education has become an important educational model and technological tool,making it easier than ever for online learners to acquire knowledge,expand their skills and receive academic education.However,the explosion in the amount of data available on online learning platforms has led to ’information overload’,making it difficult for learners to decide how to learn in the face of the vast amount of scattered learning resources available.How this content is extracted and organized is key to achieving the stated learning objectives,especially for non-experts.Providing online learners with the right learning paths is the focus of research in online education.Currently,online education researchers have generated extensive interest in knowledge graph-based learning path recommendation algorithms.Based on the above considerations,this paper proposes a knowledge graph-based learning path recommendation model and investigates a simulated annealing algorithm based on the knowledge graph for learning path planning.The main contributions of this paper are as follows.After the research on the semantic relationship of Chinese University data,this course adopts the top-down method of TFIDF data to identify different types of entity data.Firstly,this course uses the top-down method of TF-IDF data to identify this point,through many experiments,the characteristic coefficients are determined and the effectiveness of the method is verified.In the aspect of relationship extraction,based on the entity of curriculum knowledge points,the concept of correlation between courses is proposed to help extract the relationship between courses.Secondly,based on the design of curriculum knowledge map,according to the learners’ existing knowledge reserves and learning objectives,the learning path is planned through simulated annealing algorithm to minimize the number of courses they need to learn and save learners’ learning time on the basis of covering learners’ learning objectives.The recommendation results show that the model can generate and recommend qualified learning paths,so as to improve learners’ online learning experience.This paper studies the construction and application of knowledge map in the field of online courses,and puts forward a learning path recommendation method based on knowledge map,which has a certain contribution in reducing the dropout rate of learners on the online course platform and providing learning path guidance for non-professional learners. |
