Improving the Performance of a Korean Patent Document Search Model using KorPatBERT-based CPC Classification Model
The global competition for technological supremacy is intensifying, prompting every country to focus on securing technological advantages through patent acquisition. In this environment, efficient and accurate patent searching is a key factor for establishing national technological sovereignty and s...
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| Format: | Article |
| Language: | English |
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Korea Institute of Intellectual Property
2025-03-01
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| Series: | Journal of Intellectual Property |
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| Online Access: | https://jip.or.kr/2001-04/ |
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| _version_ | 1850143582870044672 |
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| author | Jaeok Min Hansung Noh Minhak Kwak Solbin Hwang Taehoon Kim |
| author_facet | Jaeok Min Hansung Noh Minhak Kwak Solbin Hwang Taehoon Kim |
| author_sort | Jaeok Min |
| collection | DOAJ |
| description | The global competition for technological supremacy is intensifying, prompting every country to focus on securing technological advantages through patent acquisition. In this environment, efficient and accurate patent searching is a key factor for establishing national technological sovereignty and strengthening global competitiveness. However, identifying prior art patents accurately and effectively within vast patent data remains a challenging task. To address this challenge, this study proposes an advanced patent search model that leverages artificial intelligence technology.
This study presents a method for creating models according to the CPC classification model based on the KorPatBERT(Korean Patent BERT) that can deeply understand the detailed technical context of patent documents through pre-training involving vast patent data. Furthermore, this study presents a method for generating high-dimensional document embedding vectors that can effectively reflect the technical subject and context of patent documents and a method for building a search system capable of processing large volumes of patent data in real time. By integrating the proposed patent search model into this system, the study successfully demonstrated improved search performance compared with existing methods in objective performance evaluations.
This study can contribute toward enhancing industrial applicability and practical usability by applying the processes of currently operational patent search data and systems. The current study’s findings are expected to provide a foundation for nations and companies to continuously lead innovation and efficiently manage and utilize patents. |
| format | Article |
| id | doaj-art-7ebf3725b87f4048ac4343f367deec7c |
| institution | OA Journals |
| issn | 1975-5945 2733-8487 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Korea Institute of Intellectual Property |
| record_format | Article |
| series | Journal of Intellectual Property |
| spelling | doaj-art-7ebf3725b87f4048ac4343f367deec7c2025-08-20T02:28:40ZengKorea Institute of Intellectual PropertyJournal of Intellectual Property1975-59452733-84872025-03-012018911710.34122/jip.2025.20.1.89Improving the Performance of a Korean Patent Document Search Model using KorPatBERT-based CPC Classification ModelJaeok Min0https://orcid.org/0000-0003-0436-164XHansung Noh1Minhak Kwak2Solbin Hwang3Taehoon Kim4Ph.D. Candidate, Dept. of Intellectual Property Convergence, Chungnam National University, Republic of Korea; Intelligent Information Strategy Dept., Korea Institute of Patent Information, Republic of KoreaPh.D. Candidate, Dept. of Intellectual Property Convergence, Chungnam National University, Republic of Korea; Intelligent Information Strategy Dept., Korea Institute of Patent Information, Republic of KoreaIntelligent Information Strategy Dept., Korea Institute of Patent Information, Republic of KoreaIntelligent Information Strategy Dept., Korea Institute of Patent Information, Republic of KoreaProfessor, Dept. of Electric, Electronic & Communication Engineering Education, College of Education, Chungnam National University, Republic of KoreaThe global competition for technological supremacy is intensifying, prompting every country to focus on securing technological advantages through patent acquisition. In this environment, efficient and accurate patent searching is a key factor for establishing national technological sovereignty and strengthening global competitiveness. However, identifying prior art patents accurately and effectively within vast patent data remains a challenging task. To address this challenge, this study proposes an advanced patent search model that leverages artificial intelligence technology. This study presents a method for creating models according to the CPC classification model based on the KorPatBERT(Korean Patent BERT) that can deeply understand the detailed technical context of patent documents through pre-training involving vast patent data. Furthermore, this study presents a method for generating high-dimensional document embedding vectors that can effectively reflect the technical subject and context of patent documents and a method for building a search system capable of processing large volumes of patent data in real time. By integrating the proposed patent search model into this system, the study successfully demonstrated improved search performance compared with existing methods in objective performance evaluations. This study can contribute toward enhancing industrial applicability and practical usability by applying the processes of currently operational patent search data and systems. The current study’s findings are expected to provide a foundation for nations and companies to continuously lead innovation and efficiently manage and utilize patents.https://jip.or.kr/2001-04/intellectual property rightspatentkorpatbertartificial intelligenceprior-art patentcpcpatent classificationpatent searchembedding vector |
| spellingShingle | Jaeok Min Hansung Noh Minhak Kwak Solbin Hwang Taehoon Kim Improving the Performance of a Korean Patent Document Search Model using KorPatBERT-based CPC Classification Model Journal of Intellectual Property intellectual property rights patent korpatbert artificial intelligence prior-art patent cpc patent classification patent search embedding vector |
| title | Improving the Performance of a Korean Patent Document Search Model using KorPatBERT-based CPC Classification Model |
| title_full | Improving the Performance of a Korean Patent Document Search Model using KorPatBERT-based CPC Classification Model |
| title_fullStr | Improving the Performance of a Korean Patent Document Search Model using KorPatBERT-based CPC Classification Model |
| title_full_unstemmed | Improving the Performance of a Korean Patent Document Search Model using KorPatBERT-based CPC Classification Model |
| title_short | Improving the Performance of a Korean Patent Document Search Model using KorPatBERT-based CPC Classification Model |
| title_sort | improving the performance of a korean patent document search model using korpatbert based cpc classification model |
| topic | intellectual property rights patent korpatbert artificial intelligence prior-art patent cpc patent classification patent search embedding vector |
| url | https://jip.or.kr/2001-04/ |
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