收稿日期: 2012-12-13
修回日期: 2013-02-21
网络出版日期: 2013-03-05
基金资助
本文系教育部人文社会科学一般项目"科学-技术关联探测方法研究——专利引文视角"(项目编号:12YJC870013)研究成果之一。
The Drawbacks and Improvement of SL Model from the Viewpoint of Optimizing Corresponding Relationships between Scientific Disciplines and Technical Domains
Received date: 2012-12-13
Revised date: 2013-02-21
Online published: 2013-03-05
科学-技术关联是指技术创新系统与科学研究系统之间的知识传递关系。探测科学-技术关联的情报学方法是:计量"论文-专利"互引信息,用专利所属的4位IPC类目与论文所属的学科之间的对应关系来反映科学-技术关联。此方法中存在两方面问题:一方面,论文被笼统地视为基础科学的代表,忽略了自然科学体系的"基础科学-技术科学-工程科学"的层级结构;另一方面,IPC类目以"功能"为分类原则且粒度过粗,难以与科学学科合理对应。对科学端的学科层级划分问题和技术端的4位IPC类目细化问题进行研究,对探测科学-技术关联的情报学方法进行改进,并以2006-2009年间的美国催化技术专利和与之具有互引关系的论文为样本进行实验,实验结果反映出更精细的学科-领域对应关系,呈现出更清晰的科学-技术关联图景。
李睿 , 容军凤 , 张玲玲 . 试论“科学-技术关联”计量模型的不足及改进——学科-领域对应优化视角[J]. 图书情报工作, 2013 , 57(05) : 86 -93 . DOI: 10.7536/j.issn.0252-3116.2013.05.016
Science Linkage (SL) means knowledge transmission between technological invention and basic science research. Based on the bidirectional citation between papers and patents, SL can be measured by the corresponding relationship between patents-owned 4-IPC category and paper disciplines. However, papers cited by patents are not all about basic research and ignores the hierarchical structure of natural science system which includes basic science, technical science and engineering science. 4-IPC is not accurate enough to identify technology, and the corresponding relationships between technical domains and scientific disciplines can hardly be established. This paper studies the subject hierarchy of the science and 4-IPC category refinement of the technology, and improves the detection of SL information science method. It takes the experiment of bidirectional citation between papers and patents of American catalytic technology from 2006 to 2009. The results show that the corresponding relationships between technical domains and scientific disciplines are established to more clearly present SL picture.
[1] Narin F, Hamilton K S,Olivastro D.Linkage between agency supported research and patented industrial technology[J].Research Evaluation,1995,5(3):183-187.
[2] CHI Research Inc. Patent technology indicators[EB/OL].[2012-11-12]. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.23.4124&rep=rep1&type=pdf.
[3] Verbeek A, Debachere K, Luwel M,et al. Linking science to technology:Using bibliographic references in patents to build linkage schemes[J].Scientometrics,2002,54(3):399-420.
[4] 黄顺基.历史上的科学分类及现代科学技术的新特点[J]. 辽东学院学报(社会科学版),2009,11(5):1-8.
[5] 王续琨.自然科学的学科层次及其相互关系[J].科学技术与辩证法,2002,19(1):58-61.
[6] 钱学森.论技术科学[J].科学通报,1957(3):97-104.
[7] Stuart T B,Podoly J M.Local search and the evolution of technological capabilities[J].Strategic Management Journal,1996,17(1):21-28.
[8] Lai Kueikuei,Wu Shiaojun.Using the patent co-citation approach to establish a new patent classification system[J].Information Processing and Management,2005,41(2):313-330.
[9] Chang Shannbin, Lai Kueikuei, Chang Shumin.Exploring technology diffusion and classification of business methods:Using the patent citation network[J]. Technological Forecasting & Social Change,2009,76(1):107-117.
[10] Kessler M M.Bibliographic coupling between scientific papers[J].American Documentation,1996,14(1):10-25.
[11] Ganzel W, Czerwon H I.A new methodological approach to bibliographic coupling and its application to the national,regional and institutional level[J].Scientometrics,1996,37(2):195-221.
[12] Huang Muhsuan, Chiang Liyun,Li Darzen,et al.Constructing a patent citation map using bibliographic coupling:A study of Taiwan’s high-tech companies[J].Scientometrics,2003,58(3):489-505.
[13] Lo Szuchia.Patent coupling analysis of primary organizations in genetic engineering research[J].Scientometrics,2008,74(1):143-151.
[14] 孙涛涛.基于专利引用计量的企业竞争情报挖掘[D].北京:中国科学院研究生院,2008.
[15] 康宇航,苏敬勤.基于专利引文的技术跟踪可视化研究共引、互引、他引、自引[J].情报学报,2009,28(2):283-289.
[16] Félix M A, Víctor H S, Evaristoas J C.A connectionist and multivariate approach to science maps:The SOM,clustering and MDS applied to libraryand information science research[J] .Journal of Information Science,2006,32(1):63-77.
[17] 魏兵,李亚非.基于同被引矩阵的专利引文分析方法[J].计算机工程与设计,2010,31(8):1779-1785.
[18] 赵党志.共引分析——研究学科及其文献结构和特点的一种有效方法[J].情报杂志, 1993,12(2):36-42.
[19] 刘青林.作品共被引分析与科学地图的绘制[J].科学学研究,2005,23(2):155-159.
[20] Rodriguez M A, Egenhofer M J.Determining Semantic similarity among entity:Lasses from different ontologies[J].IEEE Transactions on Knowledge and Data Engineering,2003,15(2):442-456.
[21] Souza X S, Davis J.Aligning ontologies and evaluating concept similarities[C]//Mersman R, Tair Z. Lecture Notes in Computer Science.Berlin:Springer-Verlag,2004:1012-1029.
[22] Lu Mingyu, Guo Chonghui, Sun Jiantao,et al.A SVM method for Web page categorization based on weight adjustment and boosting mechanism[C]//Proceedings of Fuzzy Systems and Knowledge Discovery, Berlin:Springer-Verlag, 2005:801-810.
[23] 潘跃建,王立松.改进的高精度单本体概念相似度计算模型.应用科学学报,2009,27(6):630-636.
[24] 阴国恩,安蓉,郑金香.分类中相似性的理论与模型[J].心理学探新,2005,26(1):41-43.
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