Augmented intelligence for state-of-the-art patent search

Ana Hafner; Nadja Damij; Dolores Modic

doi:10.1109/temsconeurope54743.2022.9801959

Augmented intelligence for state-of-the-art patent search

Ana Hafner, Nadja Damij^*, Dolores Modic

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

186 Downloads (Pure)

Abstract

The volume of patent data is increasing, which is a big challenge to patent examiners as well as to all inventive companies and individuals. In this paper we take the view of individual inventors who believe they invented something new. Artificial intelligence brings a promise to support their prior art search for existing (similar) inventions with machine learning and deep learning algorithms. We discuss the potential of artificial intelligence in prior art searching. We present an experiment, based on a real-life invention, comparing relevant patents we got from Boolean keyword searching with those from the semantic search supported by artificial intelligence. We can confirm that artificial intelligence has great potential in this field. However, presently it is not yet able to make traditional patent search engines obsolete, hence it still fits better with the notions of augmented intelligence or expertise.

Original language	English
Title of host publication	2022 IEEE Technology & Engineering Management Society Conference - Europe (TEMSCON-EUR)
Subtitle of host publication	Societal Challenges: Technology, Transitions and Resilience Virtual Conference
Editors	Alexander Brem, Tugrul Daim, Yogesh K. Dwivedi, Jelena Španjol, James Fleck
Place of Publication	Piscataway, US
Publisher	IEEE
Pages	61-66
Number of pages	6
ISBN (Electronic)	9781665483131
ISBN (Print)	9781665483148
DOIs	https://doi.org/10.1109/temsconeurope54743.2022.9801959
Publication status	Published - 25 Apr 2022
Event	2022 IEEE Technology and Engineering Management Conference (TEMSCON EUROPE) - Virtual, Turkey Duration: 25 Apr 2022 → 27 Apr 2022

Conference

Conference	2022 IEEE Technology and Engineering Management Conference (TEMSCON EUROPE)
Country/Territory	Turkey
Period	25/04/22 → 27/04/22

Keywords

patents
prior art search
artificial intelligence
augmented intelligence
machine learning

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10.1109/temsconeurope54743.2022.9801959

Augmented intelligence for state-of-the-art patent search_finalAccepted author manuscript, 325 KB

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Hafner, A., Damij, N., & Modic, D. (2022). Augmented intelligence for state-of-the-art patent search. In A. Brem, T. Daim, Y. K. Dwivedi, J. Španjol, & J. Fleck (Eds.), 2022 IEEE Technology & Engineering Management Society Conference - Europe (TEMSCON-EUR): Societal Challenges: Technology, Transitions and Resilience Virtual Conference (pp. 61-66). IEEE. https://doi.org/10.1109/temsconeurope54743.2022.9801959

Hafner, Ana ; Damij, Nadja ; Modic, Dolores. / Augmented intelligence for state-of-the-art patent search. 2022 IEEE Technology & Engineering Management Society Conference - Europe (TEMSCON-EUR): Societal Challenges: Technology, Transitions and Resilience Virtual Conference. editor / Alexander Brem ; Tugrul Daim ; Yogesh K. Dwivedi ; Jelena Španjol ; James Fleck. Piscataway, US : IEEE, 2022. pp. 61-66

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title = "Augmented intelligence for state-of-the-art patent search",

abstract = "The volume of patent data is increasing, which is a big challenge to patent examiners as well as to all inventive companies and individuals. In this paper we take the view of individual inventors who believe they invented something new. Artificial intelligence brings a promise to support their prior art search for existing (similar) inventions with machine learning and deep learning algorithms. We discuss the potential of artificial intelligence in prior art searching. We present an experiment, based on a real-life invention, comparing relevant patents we got from Boolean keyword searching with those from the semantic search supported by artificial intelligence. We can confirm that artificial intelligence has great potential in this field. However, presently it is not yet able to make traditional patent search engines obsolete, hence it still fits better with the notions of augmented intelligence or expertise.",

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author = "Ana Hafner and Nadja Damij and Dolores Modic",

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Hafner, A, Damij, N & Modic, D 2022, Augmented intelligence for state-of-the-art patent search. in A Brem, T Daim, YK Dwivedi, J Španjol & J Fleck (eds), 2022 IEEE Technology & Engineering Management Society Conference - Europe (TEMSCON-EUR): Societal Challenges: Technology, Transitions and Resilience Virtual Conference. IEEE, Piscataway, US, pp. 61-66, 2022 IEEE Technology and Engineering Management Conference (TEMSCON EUROPE), Turkey, 25/04/22. https://doi.org/10.1109/temsconeurope54743.2022.9801959

Augmented intelligence for state-of-the-art patent search. / Hafner, Ana; Damij, Nadja; Modic, Dolores.
2022 IEEE Technology & Engineering Management Society Conference - Europe (TEMSCON-EUR): Societal Challenges: Technology, Transitions and Resilience Virtual Conference. ed. / Alexander Brem; Tugrul Daim; Yogesh K. Dwivedi; Jelena Španjol; James Fleck. Piscataway, US: IEEE, 2022. p. 61-66.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Hafner, Ana

AU - Damij, Nadja

AU - Modic, Dolores

PY - 2022/4/25

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N2 - The volume of patent data is increasing, which is a big challenge to patent examiners as well as to all inventive companies and individuals. In this paper we take the view of individual inventors who believe they invented something new. Artificial intelligence brings a promise to support their prior art search for existing (similar) inventions with machine learning and deep learning algorithms. We discuss the potential of artificial intelligence in prior art searching. We present an experiment, based on a real-life invention, comparing relevant patents we got from Boolean keyword searching with those from the semantic search supported by artificial intelligence. We can confirm that artificial intelligence has great potential in this field. However, presently it is not yet able to make traditional patent search engines obsolete, hence it still fits better with the notions of augmented intelligence or expertise.

AB - The volume of patent data is increasing, which is a big challenge to patent examiners as well as to all inventive companies and individuals. In this paper we take the view of individual inventors who believe they invented something new. Artificial intelligence brings a promise to support their prior art search for existing (similar) inventions with machine learning and deep learning algorithms. We discuss the potential of artificial intelligence in prior art searching. We present an experiment, based on a real-life invention, comparing relevant patents we got from Boolean keyword searching with those from the semantic search supported by artificial intelligence. We can confirm that artificial intelligence has great potential in this field. However, presently it is not yet able to make traditional patent search engines obsolete, hence it still fits better with the notions of augmented intelligence or expertise.

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A2 - Brem, Alexander

A2 - Daim, Tugrul

A2 - Dwivedi, Yogesh K.

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Hafner A, Damij N, Modic D. Augmented intelligence for state-of-the-art patent search. In Brem A, Daim T, Dwivedi YK, Španjol J, Fleck J, editors, 2022 IEEE Technology & Engineering Management Society Conference - Europe (TEMSCON-EUR): Societal Challenges: Technology, Transitions and Resilience Virtual Conference. Piscataway, US: IEEE. 2022. p. 61-66 doi: 10.1109/temsconeurope54743.2022.9801959

Augmented intelligence for state-of-the-art patent search

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