Two-phase edge outlier detection method for technology opportunity discovery
| Autor: | Young-Seon Jeong, Byoung-Youl Coh, Byunghoon Kim, Jaekyung Yang, Myong K. Jeong, Jae-Min Lee, Gianluca Gazzola |
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| Rok vydání: | 2017 |
| Předmět: |
Computer science
05 social sciences General Social Sciences Technological convergence Library and Information Sciences 050905 science studies computer.software_genre Field (computer science) Computer Science Applications Data set Outlier Convergence (routing) Anomaly detection Enhanced Data Rates for GSM Evolution Data mining 0509 other social sciences 050904 information & library sciences Centrality computer |
| Zdroj: | Scientometrics. 113:1-16 |
| ISSN: | 1588-2861 0138-9130 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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