Difference between revisions of "Anticipating Technological Convergence: Link Prediction Using Wikipedia Hyperlinks"
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| − | '''Anticipating Technological Convergence: Link Prediction Using Wikipedia Hyperlinks''' - scientific work related to Wikipedia quality published in 2018, written by Juram Kim, Seungho Kim and Changyong Lee. | + | '''Anticipating Technological Convergence: Link Prediction Using Wikipedia Hyperlinks''' - scientific work related to [[Wikipedia quality]] published in 2018, written by [[Juram Kim]], [[Seungho Kim]] and [[Changyong Lee]]. |
== Overview == | == Overview == | ||
| − | Abstract Technological convergence has been the subject of many previous studies, but most have focused on ex post evaluation using patent information. The value of predictive analysis and new data sources has thus seldom been addressed. This study proposes a systematic approach to anticipating technological convergence that can be used to guide organisations towards reacting in a timely manner to challenges posed by increasingly permeable technology boundaries. For this, a technological ecology network is constructed using direct and indirect hyperlinks extracted from the Wikipedia database, and link prediction methods are employed to develop three predictive indicators of technological convergence. A case of 3D printing technology confirms, with statistically significant outcomes, that the proposed approach enables a wide-ranging search for future converging technologies. The systematic process and quantitative outcomes of the proposed approach are expected to be valuable as a complementary tool for strategic decision making regarding emerging technologies in the era of open innovation. | + | Abstract Technological convergence has been the subject of many previous studies, but most have focused on ex post evaluation using patent information. The value of predictive analysis and new data sources has thus seldom been addressed. This study proposes a systematic approach to anticipating technological convergence that can be used to guide organisations towards reacting in a timely manner to challenges posed by increasingly permeable technology boundaries. For this, a technological ecology network is constructed using direct and indirect hyperlinks extracted from the [[Wikipedia]] database, and link prediction methods are employed to develop three predictive [[indicators]] of technological convergence. A case of 3D printing technology confirms, with statistically significant outcomes, that the proposed approach enables a wide-ranging search for future converging technologies. The systematic process and quantitative outcomes of the proposed approach are expected to be valuable as a complementary tool for strategic decision making regarding emerging technologies in the era of open innovation. |
Revision as of 09:39, 7 July 2019
Anticipating Technological Convergence: Link Prediction Using Wikipedia Hyperlinks - scientific work related to Wikipedia quality published in 2018, written by Juram Kim, Seungho Kim and Changyong Lee.
Overview
Abstract Technological convergence has been the subject of many previous studies, but most have focused on ex post evaluation using patent information. The value of predictive analysis and new data sources has thus seldom been addressed. This study proposes a systematic approach to anticipating technological convergence that can be used to guide organisations towards reacting in a timely manner to challenges posed by increasingly permeable technology boundaries. For this, a technological ecology network is constructed using direct and indirect hyperlinks extracted from the Wikipedia database, and link prediction methods are employed to develop three predictive indicators of technological convergence. A case of 3D printing technology confirms, with statistically significant outcomes, that the proposed approach enables a wide-ranging search for future converging technologies. The systematic process and quantitative outcomes of the proposed approach are expected to be valuable as a complementary tool for strategic decision making regarding emerging technologies in the era of open innovation.
