Patent classification with pre-trained Bert model

dc.contributor.authorKahraman, Selen Yücesoy
dc.contributor.authorDurmuşoğlu, Alptekin
dc.contributor.authorDereli, Türkay
dc.date.accessioned2024-07-05T07:18:28Z
dc.date.available2024-07-05T07:18:28Z
dc.date.issued2024en_US
dc.departmentHKÜ, Mühendislik Fakültesi, Makine Mühendisliği Bölümüen_US
dc.description.abstractPatents 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.en_US
dc.identifier.citationKahraman 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.en_US
dc.identifier.doi10.17341/gazimmfd.1292543
dc.identifier.endpage2496en_US
dc.identifier.issn13001884
dc.identifier.issue4en_US
dc.identifier.orcid0000-0002-2130-5503en_US
dc.identifier.scopus2-s2.0-85195635887
dc.identifier.scopusqualityQ2
dc.identifier.startpage2484en_US
dc.identifier.urihttps://doi.org/10.17341/gazimmfd.1292543
dc.identifier.urihttps://hdl.handle.net/20.500.11782/4313
dc.identifier.volume39en_US
dc.identifier.wosWOS:001236221100004
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherGazi Universitesien_US
dc.relation.ispartofJournal of the Faculty of Engineering and Architecture of Gazi University
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmzHKUDK
dc.subjectBerten_US
dc.subjectdeep learningen_US
dc.subjectPatent classificationen_US
dc.subjecttext classificationen_US
dc.titlePatent classification with pre-trained Bert model
dc.typeArticle

Dosyalar

Orijinal paket

Listeleniyor 1 - 1 / 1
Yükleniyor...
Küçük Resim
İsim:
1017341gazimmfd1292543.pdf
Boyut:
597.25 KB
Biçim:
Adobe Portable Document Format
Açıklama:
Makale Dosyası

Lisans paketi

Listeleniyor 1 - 1 / 1
Yükleniyor...
Küçük Resim
İsim:
license.txt
Boyut:
1.44 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama: