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Quantitative identification of technological paradigm changes using knowledge persistence
This paper proposes a method to quantitatively identify the changes of technological paradigm over time. Specifically, the method identifies previous paradigms and predicts future paradigms by analyzing a patent citation-based knowledge network. The technological paradigm can be considered as domina...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6695126/ https://www.ncbi.nlm.nih.gov/pubmed/31415621 http://dx.doi.org/10.1371/journal.pone.0220819 |
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author | Mun, Changbae Yoon, Sejun Kim, Yongmin Raghavan, Nagarajan Park, Hyunseok |
author_facet | Mun, Changbae Yoon, Sejun Kim, Yongmin Raghavan, Nagarajan Park, Hyunseok |
author_sort | Mun, Changbae |
collection | PubMed |
description | This paper proposes a method to quantitatively identify the changes of technological paradigm over time. Specifically, the method identifies previous paradigms and predicts future paradigms by analyzing a patent citation-based knowledge network. The technological paradigm can be considered as dominantly important knowledge in a specific period. Therefore, we adopted the knowledge persistence which can quantify technological impact of an invention to recent technologies in a knowledge network. High knowledge persistence patents are dominant or paradigmatic inventions in a specific period and so changes of top knowledge persistence patents over time can show paradigm shifts. Moreover, since knowledge persistence of paradigmatic inventions are increasing dramatically faster than other ordinary inventions, recent patents having similar increasing trends in knowledge persistence with previous paradigms are identified as future paradigm inventions. We conducted an empirical case study using patents related to the genome sequencing technology. The results show that the identified previous paradigms are widely recognized as critical inventions in the domain by other studies and the identified future paradigms are also qualitatively significant inventions as promising technologies. |
format | Online Article Text |
id | pubmed-6695126 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-66951262019-08-16 Quantitative identification of technological paradigm changes using knowledge persistence Mun, Changbae Yoon, Sejun Kim, Yongmin Raghavan, Nagarajan Park, Hyunseok PLoS One Research Article This paper proposes a method to quantitatively identify the changes of technological paradigm over time. Specifically, the method identifies previous paradigms and predicts future paradigms by analyzing a patent citation-based knowledge network. The technological paradigm can be considered as dominantly important knowledge in a specific period. Therefore, we adopted the knowledge persistence which can quantify technological impact of an invention to recent technologies in a knowledge network. High knowledge persistence patents are dominant or paradigmatic inventions in a specific period and so changes of top knowledge persistence patents over time can show paradigm shifts. Moreover, since knowledge persistence of paradigmatic inventions are increasing dramatically faster than other ordinary inventions, recent patents having similar increasing trends in knowledge persistence with previous paradigms are identified as future paradigm inventions. We conducted an empirical case study using patents related to the genome sequencing technology. The results show that the identified previous paradigms are widely recognized as critical inventions in the domain by other studies and the identified future paradigms are also qualitatively significant inventions as promising technologies. Public Library of Science 2019-08-15 /pmc/articles/PMC6695126/ /pubmed/31415621 http://dx.doi.org/10.1371/journal.pone.0220819 Text en © 2019 Mun et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Mun, Changbae Yoon, Sejun Kim, Yongmin Raghavan, Nagarajan Park, Hyunseok Quantitative identification of technological paradigm changes using knowledge persistence |
title | Quantitative identification of technological paradigm changes using knowledge persistence |
title_full | Quantitative identification of technological paradigm changes using knowledge persistence |
title_fullStr | Quantitative identification of technological paradigm changes using knowledge persistence |
title_full_unstemmed | Quantitative identification of technological paradigm changes using knowledge persistence |
title_short | Quantitative identification of technological paradigm changes using knowledge persistence |
title_sort | quantitative identification of technological paradigm changes using knowledge persistence |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6695126/ https://www.ncbi.nlm.nih.gov/pubmed/31415621 http://dx.doi.org/10.1371/journal.pone.0220819 |
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