Exploring the technology emergence related to artificial intelligence: A perspective of coupling analyses

Munan Li, Wenshu Wang and Keyu Zhou

Technological Forecasting and Social Change, 2021, vol. 172, issue C

Abstract: With the spillover of the relevant knowledge on AI (artificial intelligence), an increasing number of scientific topics in the field of AI are meeting many opportunities, including transformation and applications in a multitude of areas; therefore, exploring the TE (technology emergence) and TO (technology opportunities) related to AI highlights the meaning and value. To further visualize the TE or underlying TO on AI, a perspective of coupling analyses and a computing framework on coupling relationships between publications and patents are proposed. AI has become a complicated interdisciplinarity field, and increasingly different categories are involved in the domain of AI; therefore, identifying the relevant TE or TO related to AI has become a relatively intractable but valuable problem, and our work presented in this paper can broaden the vision and bring some insights into AI development. Moreover, the proposed indicators of the coupling strength and coupling velocity and their computing methods can provide new insights or perspectives for exploring the TE or TO of a specific topic and can also enrich the relevant methodologies for technical opportunity analysis and coupling analysis between publications and patents.

Keywords: Artificial intelligence; Coupling analyses; Topic mining; LDA (Latent Dirichlet Allocation); Coupling strength; Coupling velocity (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:172:y:2021:i:c:s0040162521004960

DOI: 10.1016/j.techfore.2021.121064

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