Knowledge Graph for Multi-source Data Fusion Topics Research

Abstract

Multi-source data fusion technology is an important cornerstone of research on big data and artificial intelligence. However, due to the limitations of previous knowledge and the reliance on research methods, it has been in a state of repeated research for a long time, which has affected the long-term development of multi-source data fusion technology. With the help of Cite Space software, it is helpful to explore the path of knowledge generation for multi-source data fusion research and to tease out the development of relevant academic history. This paper analyzes 780 important papers in CNKI from 1994 to 2019. Through simple analysis, statistical analysis is performed on the number of publications, distribution of publication institutions and distribution of journals. Through author co-occurrence network analysis, visual analysis is performed on authors and teams that have significant impacts. Through keyword co-occurrence network analysis, this paper tracks the path of knowledge evolution, and explores frontier hotspots.