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Bayesian inference of spatial and temporal relations in AI patents for EU countries

Krzysztof Rusek, Agnieszka Kleszcz, Albert Cabellos-Aparicio

arXiv 18 Jan 2022 · Econometrics · publishedScientometrics (2023) · 1 citations (OpenAlex)

arXiv:2201.07168 · PDF · DOI · OpenAlex · Extracted main text

Abstract

In the paper, we propose two models of Artificial Intelligence (AI) patents in European Union (EU) countries addressing spatial and temporal behaviour. In particular, the models can quantitatively describe the interaction between countries or explain the rapidly growing trends in AI patents. For spatial analysis Poisson regression is used to explain collaboration between a pair of countries measured by the number of common patents. Through Bayesian inference, we estimated the strengths of interactions between countries in the EU and the rest of the world. In particular, a significant lack of cooperation has been identified for some pairs of countries. Alternatively, an inhomogeneous Poisson process combined with the logistic curve growth accurately models the temporal behaviour by an accurate trend line. Bayesian analysis in the time domain revealed an upcoming slowdown in patenting intensity.

Citation extraction

31
references
61
in-text mentions
40
distinct cited
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self-citations
9,735
main-text words

appendix boundary found by appendix_command · 97% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1murphy2012machine APACrefauthors Murphy, K. APACrefauthors \ (2012) 20120.81142100%
2IntellectualPropertyOffice2019 APACrefauthors IPO APACrefauthors \ (2019) 20190.73732100%
3balakrishnan1991handbook APACrefauthors Balakrishnan, N. APACrefauth… (1991) 19910.73732100%
4bayes:nature APACrefauthors van de Schoot, R. , Depaoli, S. , King,… (2021) 2021120.73732100%
5TSAY2020102000 APACrefauthors Tsay, M Y. \ Liu, Z W. APACrefauthors \ (2020) 20200.64441100%
6Copeland APACrefauthors Copeland, B. APACrefauthors \ (2020) 20200.64422100%
7gnn APACrefauthors Battaglia, P. , Hamrick, J.B.C. , Bapst, V. , San… (2018) 20180.64422100%
8daley2006introduction APACrefauthors Daley, D. \ Vere-Jones, D. APAC… (2006) 20060.58531100%
92020Natur.588S.112. APACrefauthors Wu, B. APACrefauthors \ (2020) 2020010.51121100%
10LEUSIN2020101988 APACrefauthors Leusin, M.E. , Günther, J. , Jindra,… (2020) 20200.51121100%

Showing the top 10 of 40 scored citations.