Knowledge Structure in Knowledge Discovery Patents: Visualization based on Co-word Analysis

Document Type : Research Paper

Authors

1 M.S. in Scientometrics, The Academic Institute for Ethics and Education.

2 Associate Professor, Department of library and information science. Payame Noor University, Tehran, Iran.

3 Assistant Professor of Knowledge and Information Science, Payame Noor University, Tehran, Iran.

Abstract

Purpose:The purpose of this study is to explain the structure of knowledge in the field of knowledge discovery using Co-word Analysis.
Methodology: Bibliometric methodology and social network analysis are used as the research methods. The research population consists of all keywords in 304 patents in the field of Knowledge Discovery (KD) (Reporting, knowledge discovery (KD) systems) during 1995-2014 extracted from USPTO.
Findings: Findings indicated that “System” and “Computer” are the most frequent keywords in Knowledge Discovery patents. Moreover, findings showed that “Computer***Apparatus” and “OLAP***OLAP Management” are highly frequent co-word pairs, respectively. The results of hierarchical clustering uncovered that during the 1995-2014 period 17 thematic clusters are formed. Drawing the strategic diagram showed that clusters “input devices”, “business analysis”, and “responsive modules” are among mature clusters in Knowledge Discovery.
Conclusion: The combination of concepts in this study showed that the domain of knowledge discovery is heavily dependent on computer tools, information technologies, communication technologies, and human being as the last loop in the period of systematic data analysis.

Keywords

References

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