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Artificial intelligence for patent prior art searching

Setchi, Rossitza, Spasic, Irena, Morgan, Jeffrey, Harrison, Christopher and Corken, Richard 2021. Artificial intelligence for patent prior art searching. World Patent Information 64 , 102021. 10.1016/j.wpi.2021.102021
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Abstract

This study explored how artificial intelligence (AI) could assist patent examiners as part of the prior art search process. The proof-of-concept allowed experimentation with different AI techniques to suggest search terms, retrieve most relevant documents, rank them and visualise their content. The study suggested that AI is less effective in formulating search queries but can reduce the time and cost of the process of sifting through a large number of patents. The study highlighted the importance of the humanin-the-loop approach and the need for better tools for human-centred decision and performance support in prior art searching.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Engineering
Publisher: Elsevier
ISSN: 0172-2190
Date of First Compliant Deposit: 18 February 2021
Date of Acceptance: 28 January 2021
Last Modified: 30 Mar 2021 11:30
URI: http://orca.cardiff.ac.uk/id/eprint/138650

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