Intellectual Structure of Research on Data Mining Using Bibliographic Coupling Analysis

Abstract

With the rapid development of mobile Internet, the growth amount of data has exploded, and data mining has played an increasingly important role in data analyzing. More and more researches have been done on data mining. Detecting intellectual structure of data mining research is of significance in understanding its research topics and research fronts. Focusing on the method of bibliographic coupling analysis, this paper explores the intellectual structure of data mining during 2007-2016, based on 12625 cleaned bibliographic data of data mining-related articles retrieved from Web of Science. Experiments results show that there are mainly 10 research topics in the field of data mining, such as classification, frequent pattern mining and clustering, among which the first three topics are the research on domain of data mining itself, and the last seven topics are the research on data mining applications.