Patent classification with pre-trained Bert model

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Gazi Universitesi

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info:eu-repo/semantics/openAccess

Abstract

Patents are documents that help protect innovations in information technologies and grant special rights to the creator of these innovations for a certain period of time. While these rights give the patent owner the right to use the innovation commercially, they prevent others from using the innovation without permission. Radical innovations and ground-breaking technological advances are derived from technical information contained in existing patents. Using an automatic classification system, patents assigned to the technical class to which they belong can pave the way for researchers and provide an environment in which they can create new inventions. This study presents an automatic patent classification analysis using the BERT algorithm. Hyperparameter analyses are also preferred in this study in order to achieve more successful prediction accuracy in automatic patent classification problems. The obtained results were at a level that competed with those in the literature. An accuracy of 58% was achieved at the subclass level. © 2024 Gazi Universitesi. All rights reserved.

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Bert, deep learning, Patent classification, text classification

Journal or Series

Journal of the Faculty of Engineering and Architecture of Gazi University

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Volume

39

Issue

4

Citation

Kahraman S.Y., Durmusoglu A. & Dereli T. (2024). Patent classification with pre-trained Bert model. Journal of the Faculty of Engineering and Architecture of Gazi University. ( 39, 4, 2484-2496.). https://doi.org/10.17341/gazimmfd.1292543.

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