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Identification of data mining research frontier based on conference papers
- Source :
- International Journal of Crowd Science. 5:143-153
- Publication Year :
- 2021
- Publisher :
- Tsinghua University Press, 2021.
-
Abstract
- Purpose Identifying the frontiers of a specific research field is one of the most basic tasks in bibliometrics and research published in leading conferences is crucial to the data mining research community, whereas few research studies have focused on it. The purpose of this study is to detect the intellectual structure of data mining based on conference papers. Design/methodology/approach This study takes the authoritative conference papers of the ranking 9 in the data mining field provided by Google Scholar Metrics as a sample. According to paper amount, this paper first detects the annual situation of the published documents and the distribution of the published conferences. Furthermore, from the research perspective of keywords, CiteSpace was used to dig into the conference papers to identify the frontiers of data mining, which focus on keywords term frequency, keywords betweenness centrality, keywords clustering and burst keywords. Findings Research showed that the research heat of data mining had experienced a linear upward trend during 2007 and 2016. The frontier identification based on the conference papers showed that there were five research hotspots in data mining, including clustering, classification, recommendation, social network analysis and community detection. The research contents embodied in the conference papers were also very rich. Originality/value This study detected the research frontier from leading data mining conference papers. Based on the keyword co-occurrence network, from four dimensions of keyword term frequency, betweeness centrality, clustering analysis and burst analysis, this paper identified and analyzed the research frontiers of data mining discipline from 2007 to 2016.
- Subjects :
- Computer science
020206 networking & telecommunications
Sample (statistics)
02 engineering and technology
Bibliometrics
computer.software_genre
Field (computer science)
Ranking (information retrieval)
Identification (information)
Betweenness centrality
0202 electrical engineering, electronic engineering, information engineering
Computer Science (miscellaneous)
Business, Management and Accounting (miscellaneous)
020201 artificial intelligence & image processing
Decision Sciences (miscellaneous)
Data mining
Cluster analysis
Social network analysis
computer
Subjects
Details
- ISSN :
- 23987294
- Volume :
- 5
- Database :
- OpenAIRE
- Journal :
- International Journal of Crowd Science
- Accession number :
- edsair.doi...........8d32b7da1f613d4e1d3370f337129a54