The Personalized Learning Paths for Digital Media Technology Education based on Big Data

Abstract

The paper intends to study the evolution of domain knowledge by studying the spatial-temporal collaborative model. A joint knowledge network model based on the time-space domain is proposed to represent the knowledge base. The skeletal clustering algorithm analyzes the evolution of knowledge networks over the years. According to the concept of the evolution process of knowledge, the paper makes a connection and path analysis of its evolution track. An empirical study of the digital media field is carried out. The results show that the algorithm proposed in this paper can extract the evolution trajectory of domain knowledge that varies with year. The path of knowledge evolution can show the correlation between research topics, hot topics, core literature, the evolution law of research topics and research methods of multiple disciplines, and the cross-characteristics of multiple disciplines.