Review of Latent Knowledge Discovery Methods Based on Association Between Scientific Papers and Technology Patents
Wang Shiwei1,2,Chen Chun1,2()
1Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China 2Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
【目的】 通过文献调研梳理总结基于科学论文和技术专利的潜在知识发现方法，总结研究不足和未来发展方向。【文献范围】 以Patents and Papers，Science and Technology，Knowledge Discovery，专利和论文，科学和技术，知识发现等为关键词分别在Web of Science、Springer Link和CNKI等学术平台检索文献，筛选出75篇具有代表性的文献进行综述。【方法】 在科学-技术关联关系的基础上，从数据关联、主体关联、主题关联以及多维度关联4方面对文献进行归纳梳理。【结果】 现有研究方法存在不足，包括识别语料的数据来源具有局限性且异构数据源的不规范性；识别方法的潜在知识发现语义性不足、粒度较粗；基于论文和专利的知识体系和测度指标不完善；识别结果缺乏全面性、动态性、探索性。【局限】 主要选取部分代表性文献进行综述，深入阐述不够深刻；在内容分析层面上，科学-技术关联关系的多策略综合分析方法是目前的热点研究，本文对此方法分析系统性不足；对检索得出的代表性综述文献的选择具有一定的主观性。【结论】 在未来的研究中要整合多源数据库资源并规范化异构数据，增强识别方法的语义分析能力和细化识别粒度，完善知识组织体系并丰富测度指标，加强对潜在知识发现动态演变的研究。
[Objective] This paper reviews the latent knowledge discovery methods based on scientific papers and technology patents to identify deficiencies in current studies and future development directions.[Coverage] A total of 75 representative articles were retrieved using keywords such as “Patents and Papers”, “Science and Technology”, and “Knowledge Discovery” from the Web of Science, Springer Link, and CNKI. [Methods] Based on the scientific-technical association, we reviewed the literature from four aspects: data association, subject association, theme association, and multi-dimensional association. [Results] The existing research methods have limitations, such as the need for more data sources for identifying corpus and the non-standardization of heterogeneous data sources. The potential knowledge discovery of the recognition method needs more semantics and better granularity. The knowledge system and measurement index based on papers and patents still need to be completed. The recognition results need more comprehensiveness, dynamic and exploratory nature. [Limitations] Mainly select some representative literature to review, in-depth elaboration is not deep enough. At the level of content analysis, the multi-strategy comprehensive analysis method of science-technology correlation is a hot research at present, but the analysis of this method is not systematic enough in this paper. The selection of representative review literature obtained from the search has a certain degree of individual subjectivity. [Conclusions] In future research, we should integrate multi-source databases and standardize heterogeneous data, enhance the semantic analysis ability of recognition methods, and refine the recognition granularity. We also need to improve the knowledge organization system, enrich the measurement indicators, and strengthen the research on the dynamic evolution of latent knowledge discovery.
王诗炜, 陈春. 基于科学论文和技术专利关联关系识别潜在知识发现方法研究综述*[J]. 数据分析与知识发现, 2023, 7(7): 18-31.
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