Ön eğitimli Bert modeli ile patent sınıflandırılması
Year 2024,
Volume: 39 Issue: 4, 2484 - 2496, 20.05.2024
Selen Yücesoy Kahraman
,
Alptekin Durmuşoğlu
,
Türkay Dereli
Abstract
Patentler, bilgi teknolojilerindeki yeniliklerin korunmasına yardımcı olan ve bu yeniliklerin yaratıcısına belirli bir süre boyunca özel haklar sağlayan belgelerdir. Bu haklar, patent sahibine yeniliği ticari olarak kullanma hakkı verirken, başkalarının yeniliği izinsiz kullanmasını engeller. Radikal yenilikler ve çığır açan teknolojik gelişmeler, mevcut patentlerde yer alan teknik bilgilerden türetilmiştir. Otomatik bir sınıflandırma sistemi kullanılarak, ait oldukları teknik sınıfa atanan patentler, araştırmacıların önünü açabilmekte ve yeni buluşlar yaratabilecekleri bir ortam sağlayabilmektedir. Bu çalışma, BERT algoritmasını kullanarak otomatik bir patent sınıflandırma analizi sunmaktadır. Otomatik patent sınıflandırma problemlerinde daha başarılı tahmin doğruluğuna ulaşabilmek için yapılan hiper parametre analizleri bu çalışmada da tercih edilmiştir. Elde edilen sonuçlar literatürdeki sonuçlarla rekabet edecek düzeydedir. Bu çalışmada alt sınıf düzeyinde % 55,9 tahmin doğruluğu elde edilmiştir.
Supporting Institution
Destekleyen bir kurum bulunmamaktadır.
Project Number
Proje numarası bulunmamaktadır.
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Year 2024,
Volume: 39 Issue: 4, 2484 - 2496, 20.05.2024
Selen Yücesoy Kahraman
,
Alptekin Durmuşoğlu
,
Türkay Dereli
Project Number
Proje numarası bulunmamaktadır.
References
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- 26. Wu, C., Ken, Y., Huang, T, Patent classification system using a new hybrid genetic algorithm support vector machine, Applied Soft Computing 10, 4, 1164-1177, 2010.
- 27. Hu, J., Li, S., Hu, J., and Yang, G., A hierarchical feature extraction model for multi-label mechanical patent classification, Sustainability, 10 (1), 1-22, 2018.
- 28. Alla G. Kravets, Nikita Lebedev, and Maxim Legenchenko, Patents images retrieval and convolutional neural network training dataset quality improvement, IV International Research Conference Information Technologies in Science, Management, Social Sphere and Medicine ITSMSSM 2017, 287–293, 2017.
- 29. Wang, Y., Du, J., Shao, Y., Li, A., and Xu, X., A Patent Text Classification Method Based on Phrase-Context Fusion Feature.", Proceedings of 2021 Chinese Intelligent Automation Conference, Deng Z., Springer, Singapore, 157-164, 2022.
- 30. Kantar O., Kilimci Z.H., Deep learning based hybrid gold index (XAU/USD) direction forecast model, Journal of the Faculty of Engineering and Architecture of Gazi University, 38 (2), 1117–1128, 2022.
- 31. Sanh, V., Debut, L., Chaumond, J., and Wolf, T. DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter, https://arxiv.org/abs/1910.01108, Yayın tarihi Ekim 2019, Güncelleme Tarihi, Mart 2020, Erişim Tarihi Temmuz 25, 2023.
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- 34. Li, S., Hu, J., Cui, Y., and Hu, J., DeepPatent: patent classification with convolutional neural networks and word embedding. Scientometrics, 117 (2), 721–744, 2018.
- 35. Lim, S., and Kwon, Y., IPC multi-label classification applying the characteristics of patent documents, Advances in Computer Science and Ubiquitous Computing. UCAWSN CUTE CSA 2016, Park, J., Lecture Notes in Electrical Engineering, Springer, Singapore, 421, 166–172, 2017.
- 36. Hu, J., Li, S., Hu, J., and Yang, G., A Hierarchical Feature Extraction Model for Multi-Label Mechanical Patent Classification, Sustainability, 10 (1), 219,2018.
- 37. Lee, J.S., and Hsiang, J., Patent classification by fine-tuning BERT language model, World Patent Information, 61, 101965, 2020.
- 38. Fall, C.J., Törcsvári, A., Benzineb, K., and Karetka, G., Automated categorization in the international patent classification, ACM SIGIR Forum, 37 (1), 10–25, 2003.
- 39. Qiu, X., Huang, X.-J., Liu, Z., and Zhou, J., Hierarchical Text Classification with Latent Concepts, Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: short papers 598–602, Portland, Oregon, 19-24 Haziran 2011.
- 40. Seneviratne, D., Geva, S., Zuccon, G., Ferraro, G., and Meireles, M., Linking patents to knowledge sources: A context matching technique using automatic patent classification, Proceedings of the 23rd Australasian Document Computing Symposium, 1-4, 2018.
- 41. Aiolli, F., Cardin, R., Sebastiani, F., and Sperduti, A., Preferential Text Classification: Learning Algorithms and Evaluation Measures, Information retrieval, 12, 559–580, 2009.
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