Personalized recommendation method of educational information resources based on knowledge graph
Due to the low accuracy of existing recommendation methods,a personalized recommendation method of educational information resources based on knowledge graph is proposed in this paper.Firstly,user behavior datas of educational information resources are collected through collaborative filtering to obtain users'interests and preferences.Then,the knowledge graph is used to calculate the matching degree between user interests and resource entity attributes,and obtain the matching degree between resource entities and semantic relationship attributes.Finally,by matching the characteristics of users and educational information resources,comparing the membership values of different recommendation results,determing the degree of matching with user interests,the personalized recommendation results are generated.The experimental results show that the sparsity of the experimental group is 80%,and the recommendation accuracy is 96.3%,the proposed method can achieve the good matching effect and provide more accurate recommendation content.
knowledge mapeducational information resourcespersionalized recommendation
NETL
NSTL
万方数据
