Abstract Knowledge flow between papers and patents reflects the evolutionary route of scientific research and technological innovation. Category mapping analysis of Chinese Library Classification (CLC) and International Patent Classification (IPC) is helpful in breaking through the barriers between paper and patent resources, by identifying the characteristics of scientific and technological development between papers and patents of different disciplines. This study proposes a mapping method that integrates the idea of social network analysis with co-occurrence mapping. Taking the papers and patents of the same author and highly related research topics as unit data, CLC and IPC are used to classify and label each unit of data simultaneously, thereby combining category similarity calculations and analyzing the labeling results of the dataset. Finally, universal one-to-one, one-to-many, and two-way mappings between the CLC and IPC categories are obtained.
Song Yanhui,Chen Xinqi. Co-occurrence Mapping between Chinese Library Classification and International Patent Classification Categories Based on Author's Research Similarity[J]. 情报学报, 2024, 43(8): 927-935.
1 Bhattacharya S, Kretschmer H, Meyer M. Characterizing intellectual spaces between science and technology[J]. Scientometrics, 2003, 58(2): 369-390. 2 de Solla Price D J. Is technology historically independent of science? A study in statistical historiography[J]. Technology and Culture, 1965, 6(4): 553-568. 3 孙笑明, 崔文田, 林军. 一种网络展现文献检索结果的理论模型[J]. 情报学报, 2011, 30(2): 146-154. 4 司莉. 知识组织系统的互操作及其实现[J]. 现代图书情报技术, 2007(3): 29-34. 5 Xu S, Li L, An X, et al. An approach for detecting the commonality and specialty between scientific publications and patents[J]. Scientometrics, 2021, 126(9): 7445-7475. 6 马文峰. 数字资源整合研究[J]. 中国图书馆学报, 2002, 28(4): 64-67. 7 廖腾芳. 等级列举式分类法存在的问题与分面组配后标引的分布研究[J]. 情报科学, 2003, 21(11): 1181-1184. 8 于红, 胡安朋. 对《国际专利分类表》第七版一些变化的研究[J]. 情报理论与实践, 2002, 25(3): 203-206. 9 黄月. IPC与中图法编制体例特征差异[J]. 中国民航学院学报, 2005, 23(S1): 277-278. 10 国家图书馆《中国图书馆分类法》编辑委员会. 中国图书馆分类法[M]. 5版. 北京: 国家图书馆出版社, 2010. 11 李悦, 苏成, 潘云涛. 分类法映射研究综述[J]. 情报理论与实践, 2018, 41(9): 154-160. 12 原小玲. DDC22与CLC5化学类目映射分析[J]. 图书馆理论与实践, 2013(3): 71-74. 13 Ba Z C, Liang Z T. A novel approach to measuring science-technology linkage: From the perspective of knowledge network coupling[J]. Journal of Informetrics, 2021, 15(3): 101167. 14 Trappey C V, Trappey A J C, Chen L W L. Computer-supported portfolio analysis and comparison using ontology-based patent classification mapping scheme: the case of mobile communication patent pools[J]. Cluster Computing, 2017, 20(2): 1661-1677. 15 Gao F, Chen D L, Weng M H, et al. Revealing development trends in blockchain-based 5G network technologies through patent analysis[J]. Sustainability, 2021, 13(5): 2548. 16 Jin Y C, Liu J Z, Wang X H, et al. Technology recommendations for an innovative agricultural robot design based on technology knowledge graphs[J]. Processes, 2021, 9(11): 1905. 17 Liu L F, Li Y, Xiong Y, et al. A new function-based patent knowledge retrieval tool for conceptual design of innovative products[J]. Computers in Industry, 2020, 115: 103154. 18 蒋彦廷, 吴钰洁. 英文文献的《中图法》分类号自动标注研究——基于文本增强与类目映射策略[J]. 数字图书馆论坛, 2022(5): 39-46. 19 刘晓鹏, 真溱, 于洋. 利用关键词实现知识组织系统自动映射的方法[C]// 数字图书馆高层论坛2010年年会论文集. 北京: 中国科学技术出版社, 2010: 119-123. 20 Xu H Y, Yue Z H, Pang H S, et al. Integrative model for discovering linked topics in science and technology[J]. Journal of Informetrics, 2022, 16(2): 101265. 21 Du W, Cheng X S, Yang C, et al. Establishing interoperability among knowledge organization systems for research management: a social network approach[J]. Scientometrics, 2017, 112(3): 1489-1506. 22 毛云莹, 陆伟. 基于IPC关联的专利技术和产业双向分析框架研究[J]. 情报科学, 2022, 40(4): 33-39. 23 周林志. 国际专利分类法与中图分类法类目映射研究[D]. 北京: 北京林业大学, 2010. 24 李珂, 宋文. 农业科学领域DDC和CLC类目映射分析[J]. 图书馆理论与实践, 2015(10): 58-62. 25 靳雪茹, 齐建东, 王立臣, 等. 基于机器学习的类目映射方法——国际专利分类法与中国图书馆分类法[J]. 计算机应用, 2011, 31(7): 1781-1784. 26 何贤敏, 李茂西, 何彦青. 基于孪生BERT网络的科技文献类目映射[J]. 计算机研究与发展, 2021, 58(8): 1751-1760. 27 Chen X, Ye P F, Huang L, et al. Exploring science-technology linkages: a deep learning-empowered solution[J]. Information Processing & Management, 2023, 60(2): 103255. 28 马晓萌, 徐峰, 刘清民, 等. 基于doc2vec的专利与行业类目映射研究[J]. 情报探索, 2020(6): 67-74. 29 徐烨, 肖明. CLC与LCC类目同现映射方法研究——以图情领域为例[J]. 图书馆论坛, 2019, 39(12): 11-17, 143. 30 陈瑞, 贾君枝. 基于众包模式的分类法映射研究[J]. 情报理论与实践, 2020, 43(7): 137-143. 31 赖院根. 期刊论文与专利文献的链接研究[J]. 图书情报知识, 2011(1): 63-69.
