Multi label classification of Artificial Intelligence related patents using Modified D2SBERT and Sentence Attention mechanism
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Abstract (arXiv)
Patent classification is an essential task in patent information management and patent knowledge mining. It is very important to classify patents related to artificial intelligence, which is the biggest topic these days. However, artificial intelligence-related patents are very difficult to classify because it is a mixture of complex technologies and legal terms. Moreover, due to the unsatisfactory performance of current algorithms, it is still mostly done manually, wasting a lot of time and money. Therefore, we present a method for classifying artificial intelligence-related patents published by the USPTO using natural language processing technique and deep learning methodology. We use deformed BERT and sentence attention overcome the limitations of BERT. Our experiment result is highest performance compared to other deep learning methods.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 7 of its 33 references that are in the map. First posted on arXiv 3 Mar 2023.
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7 of 33 references.
References · 7
- 2018Explainable Prediction of Medical Codes from Clinical Textcited by 234
- 2019DocBERT: BERT for Document Classificationcited by 68
- 2017Multi-Label Classification of Patient Notes a Case Study on ICD Code Assignmentcited by 37
- 2021PatentSBERTa: A Deep NLP based Hybrid Model for Patent Distance and Classification using Augmented SBERTcited by 24
- 2021An Explainable CNN Approach for Medical Codes Prediction from Clinical Textcited by 9
- 2021Medical Code Prediction from Discharge Summary: Document to Sequence BERT using Sequence Attentioncited by 3
- 2022DAGAM: Data Augmentation with Generation And Modificationcited by 2
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Citing papers per year: 2023: 1; 2024: 1.
2 papers.