Two-phase edge outlier detection method for technology opportunity discovery

Byunghoon Kim, Gianluca Gazzola, Jaekyung Yang, Jae-Min Lee, Byoung-Youl Coh, Myong K. Jeong and Young-Seon Jeong ()
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Byunghoon Kim: Korea Institute of Science and Technology Information
Gianluca Gazzola: Rutgers Business School
Jaekyung Yang: Chonbuk National University
Jae-Min Lee: Korea Institute of Science and Technology Information
Byoung-Youl Coh: Korea Institute of Science and Technology Information
Myong K. Jeong: Rutgers University
Young-Seon Jeong: Chonnam National University

Scientometrics, 2017, vol. 113, issue 1, No 1, 16 pages

Abstract: Abstract This article introduces a method for identifying potential opportunities of innovation arising from the convergence of different technological areas, based on the presence of edge outliers in a patent citation network. Edge outliers are detected via the assessment of their centrality; pairs of patents connected by edge outliers are then analyzed for technological relatedness and past involvement in technological convergence. The pairs with the highest potential for future convergence are finally selected and their keywords combined to suggest new directions of innovation. We illustrate our method on a data set of US patents in the field of digital information and security.

Keywords: Edge outlier; Outlier detection; Technology convergence; Technology opportunity discovery; Patent citation network (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s11192-017-2472-1

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