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MEASURING PATENT NOVELTY USING NATURAL LANGUAGE PROCESSING

Published online by Cambridge University Press:  19 June 2023

Ali Yassine and
Carlo Lipizzi
Ali Yassine*
Affiliation:
Stevens Institute of Technology
Carlo Lipizzi
Affiliation:
Stevens Institute of Technology
*
Yassine, Ali, Stevens Institute of Technology, United States of America, ayassine@stevens.edu

Abstract

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This paper develops a novelty measure for patents. We devise a text-based novelty measure using natural language processing (NLP) techniques. The proposed method is applied on patents that belong to a common category, which represents a subset of patents under a specific patent class. We then extract the novelty-value profile of those patents and discuss a use case for product design and development (i.e., extracting patent novelty and predicting inventive value).

Keywords

New product developmentMachine learningOpen source design

Information

Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023, pp. 2605 - 2614
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

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