Knowledge Graph Based Recommendation Algorithm for Educational Resource
Yajie Ma, Bin Liu, Weihua Huang, Feng Dan · 2022
Connecting the educational resources of specific disciplines to form a knowledge network is a key step in the intellectualization of education and research. Based on a knowledge graph of power grid technology education resources of 42510 literature and information in China National Knowledge Infrastructure (CNKI) in our former research, a recommendation algorithm is proposed in this paper. The algorithm aims at the problem of data sparsity and cold start of traditional recommendation algorithm, which adopts hybrid similarity fusion to quickly match core resources and improve the pertinence and efficiency of education and research. The work in this paper show that the integration of knowledge graph technology and academic literature database can provide scientific and intelligent data analysis methods for discipline education and research.