A novel patent technology characterization method based on heterogeneous network message passing algorithm and patent classification system
Patents are widely recognized as important data for generating innovation. Accurate and rational characterizing patent technology content is a prerequisite for applying innovation generation algorithms. Existing research widely employs classification codes that annotate the technology content of pat...
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| Published in: | Expert systems with applications Vol. 256; p. 124895 |
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| Main Authors: | , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Ltd
05.12.2024
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| Subjects: | |
| ISSN: | 0957-4174 |
| Online Access: | Get full text |
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| Abstract | Patents are widely recognized as important data for generating innovation. Accurate and rational characterizing patent technology content is a prerequisite for applying innovation generation algorithms. Existing research widely employs classification codes that annotate the technology content of patents to represent patents. However, the oversight of technology similarity information within patent classification systems results in deficiencies in the accuracy and effectiveness of their representations. To fill this research gap, we analyze the hierarchical structure of patent classification systems to extract the technology similarity information embedded within them. Then, we propose a novel patent technology characterization method based on the heterogeneous network message passing algorithm, which integrates the technology similarity information in the classification code co-occurrence information and the patent classification system to obtain a more accurate patent characterization. Subsequently, several evaluation experiments were conducted to compare our method with typical existing methods. The results demonstrate that our method outperforms these methods in accuracy and effectiveness. Finally, we conducted a case study to validate the reliability and practicality of our approach. In summary, our method exhibited superior performance, thereby providing robust support for innovation generation methods based on patent characterization, with high application value and extension prospects. |
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| AbstractList | Patents are widely recognized as important data for generating innovation. Accurate and rational characterizing patent technology content is a prerequisite for applying innovation generation algorithms. Existing research widely employs classification codes that annotate the technology content of patents to represent patents. However, the oversight of technology similarity information within patent classification systems results in deficiencies in the accuracy and effectiveness of their representations. To fill this research gap, we analyze the hierarchical structure of patent classification systems to extract the technology similarity information embedded within them. Then, we propose a novel patent technology characterization method based on the heterogeneous network message passing algorithm, which integrates the technology similarity information in the classification code co-occurrence information and the patent classification system to obtain a more accurate patent characterization. Subsequently, several evaluation experiments were conducted to compare our method with typical existing methods. The results demonstrate that our method outperforms these methods in accuracy and effectiveness. Finally, we conducted a case study to validate the reliability and practicality of our approach. In summary, our method exhibited superior performance, thereby providing robust support for innovation generation methods based on patent characterization, with high application value and extension prospects. |
| ArticleNumber | 124895 |
| Author | Chang, Zhi-Xing Guo, Wei Ma, Jian Zhang, Guan-Wei Wang, Lei Wang, Zi-Liang Fu, Zhong-Lin |
| Author_xml | – sequence: 1 givenname: Zhi-Xing surname: Chang fullname: Chang, Zhi-Xing email: Sean_key@tju.edu.cn organization: Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, China – sequence: 2 givenname: Wei surname: Guo fullname: Guo, Wei email: wguo@tju.edu.cn organization: Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, China – sequence: 3 givenname: Lei orcidid: 0000-0001-5205-2951 surname: Wang fullname: Wang, Lei email: tjuwl@tju.edu.cn organization: Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, China – sequence: 4 givenname: Zhong-Lin orcidid: 0000-0002-2412-1232 surname: Fu fullname: Fu, Zhong-Lin email: zhonglin_fu@tju.edu.cn organization: Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, China – sequence: 5 givenname: Jian orcidid: 0000-0002-3370-1431 surname: Ma fullname: Ma, Jian email: jacksonma@tju.edu.cn organization: Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, China – sequence: 6 givenname: Guan-Wei surname: Zhang fullname: Zhang, Guan-Wei email: zhangguanwei@tju.edu.cn organization: Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, China – sequence: 7 givenname: Zi-Liang surname: Wang fullname: Wang, Zi-Liang email: wzl07@tju.edu.cn organization: Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, China |
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