知识组织

科技文献知识基因表达及遗传与变异研究

  • 白如江 ,
  • 张庆芝 ,
  • 孙一钢
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  • 1. 国家图书馆 北京 100081;
    2. 山东理工大学科技信息研究所 淄博 255049;
    3. 北京大学信息管理系 北京 100871
白如江(ORCID:0000-0003-3822-8484),副研究馆员,硕士生导师,博士;孙一钢(ORCID:0000-0001-8478-1737),副馆长,研究馆员,博士。

收稿日期: 2019-05-08

  修回日期: 2019-10-08

  网络出版日期: 2020-02-20

基金资助

本文系中国博士后科学基金项目"基于知识基因表达的科技创新路径识别研究"(项目编号:2018M640101)研究成果之一。

A Study of Knowledge Meme Heredity and Mutation in Academic Paper

  • Bai Rujiang ,
  • Zhang Qingzhi ,
  • Sun Yigang
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  • 1. National Library of China, Beijing 100081;
    2. Institute of Scientific and Technical Information, Shandong University of Technology, Zibo 25000;
    3. Department of Information Management, Peking University, Beijing 100871

Received date: 2019-05-08

  Revised date: 2019-10-08

  Online published: 2020-02-20

摘要

[目的/意义] 知识的积累与传承推动着人类社会的发展,为此提出利用科技文献知识基因进行知识的遗传与变异研究,以期对知识传承与发展变化进行更直观、全面地透视。[方法/过程] 通过辨析知识基因概念,确定知识基因的研究意义,并探讨其具体研究对象;提出科技文献知识基因内容表达的两种方式,归纳科技文献知识基因的类型;分析影响知识基因遗传与变异的主要因素,且设计识别知识基因的遗传与变异的方法。[结果/结论] 通过对科技文献知识基因的辨识,能够有效揭示出不同文献之间的知识传承与迭代,促进知识基因理论体系的发展与完善。

本文引用格式

白如江 , 张庆芝 , 孙一钢 . 科技文献知识基因表达及遗传与变异研究[J]. 图书情报工作, 2020 , 64(4) : 78 -87 . DOI: 10.13266/j.issn.0252-3116.2020.04.009

Abstract

[Purpose/significance] The accumulation and inheritance of knowledge promotes the development of human society. This paper proposes to study the inheritance and variation of knowledge by using the knowledge gene of scientific and technological literature, in order to have a more intuitive and comprehensive perspective on the inheritance and development of knowledge.[Method/process] By analyzing the narrow and broad definitions of knowledge genes, the research significance of knowledge genes was determined and their specific research objects were discussed. Two ways of expression of knowledge genes in scientific and technological literature were proposed, and the types of knowledge genes in scientific and technological literature were analyzed. The main factors affecting the inheritance and variation of knowledge genes were summarized, and the inheritance of knowledge genes was designed. And the method of variation.[Result/conclusion] The identification of knowledge genes in scientific and technological literature can effectively reveal the knowledge inheritance and iteration between different documents, and promote the development and perfection of the theoretical system of knowledge memes.

参考文献

[1] MARTIN W B. Atoms, bytes and genes public resistance and techno-scientific responses[M]. New York:Routledge,2015:1.
[2] MANDELBROT B. How long is the coast of Britain? statistical self-similarity and fractional dimension[J]. Science, 1967, 156(3775):636-638.
[3] SIDDHARTHA M. The gene:an intimate history[M] New York:Scribner,2017:121.
[4] 道金斯.自私的基因[M].卢允中,译.长春:吉林人民出版社,1998:192.
[5] JAMES G. The information:a history, a theory, a flood[M]. New York:Books,2012:307-320.
[6] HERRNSTEIN R, MURRAY C. The bell curve:intelligence and class structure in American life.[J]. Transforming Anthropology, 2010, 6(1/2):87-89.
[7] SEN S K. A note on the idea gene and its relevance to information science[J]. ALIS, 1981, 28(1/4):97-102.
[8] BLACKMORE S. The meme machine[M]. Oxford:Oxford Paperbacks, 2000.
[9] AUNGER R. The electric meme:a new theory of how we think[M]. New York:Simon and Schuster, 2002.
[10] DALTON C, JASON F. The genome factor:what the social genomics revolution reveals about ourselves, our history, and the future[M]. Princeton:Princeton University Press,2017:4,284.
[11] 李伯文.论科学的"遗传"和"变异"[J].科学学与科学技术管理,1985(10):21-25.
[12] 刘植惠.知识基因理论新进展[J].情报科学,2003(12):1243-1245.
[13] 刘植惠.知识基因理论的由来、基本内容及发展[J].情报理论与实践,1998(2):8-13.
[14] 刘植惠.知识基因探索(一)[J].情报理论与实践,1998(1):63-65.
[15] SUN X L, DING K. Identifying and tracking scientific and technological knowledge memes from citation networks of publications and patents[J]. Scientometrics,2018,116(3):1735-1748.
[16] 刘则渊.知识基因论视野下的"新兴研究领域识别计量"著作-《新兴研究领域识别计量》序言[M].北京:科学出版社,2017:ⅰ-ⅵ.
[17] 和金生,吕文娟.知识基因论的源起、内容与发展[J].科学学研究,2011,29(10):1454-1459.
[18] 许琦,顾新建.一种基于Subject-Action-Object三元组的知识基因提取方法[J].浙江大学学报(工学版),2013,47(3):385-399.
[19] 孙晓玲,丁堃.基于知识基因发现的科学与技术关系研究[J].情报理论与实践, 2017,40(6):23-26,17.
[20] 逯万辉,谭宗颖.基于知识基因游离与重组的领域主题演化研究[J].情报理论与实践,2019,42(2):101-107.
[21] 吴军.见识:商业的本质和人生的智慧[M].北京:中信出版社,2017:42-46.
[22] 索传军,盖双双.知识元的内涵、结构与描述模型研究[J].中国图书馆学报, 2018,44(4):54-72.
[23] RICE W R. Sex chromosomes and the evolution of sexual dimorphism[J]. Evolution, 1984, 38(4):735-742.
[24] 傅荣贤.论古代提要和现代摘要的文献观[J].图书情报工作,2016,60(6):26-31.
[25] 祝清松,冷伏海.引文内容分析方法研究综述[J].情报资料工作,2013(5):39-43.
[26] 徐雷,潘珺.知识网络等相关概念比较分析[J].情报科学,2017,35(12):10-15.
[27] RASKIN R. Enabling semantic interoperability for earth system science[C]//American Geophysical Union.AGU Fall Meeting Abstracts. New York:American Geophysical Union. 2004:11-16
[28] 张运良,徐硕,朱礼军,等.汉语科技词系统——一种可用于科技信息资源深度内容分析的语义资源[J].图书情报工作,2011,55(4):100-105.
[29] MA X, CARRANZA E J M, WU C, et al. A SKOS-based multilingual thesaurus of geological time scale for interoperability of online geological maps[J]. Computers & geosciences, 2011, 37(10):1602-1615.
[30] MOINE M P, VALCKE S, LAWRENCE B N, et al. Development and exploitation of a controlled vocabulary in support of climate modelling[J]. Geoscientific model development, 2014, 7(2):479-493.
[31] SU Y, ANDREWS J, HUANG H, et al. Reengineering of MeSH thesauri for term selection to optimize literature retrieval and knowledge reconstruction in support of stem cell research[J]. BMC medical informatics and decision making, 2016, 16(1):54.
[32] MORAVCSIK M J, MURUGESAN P. Some results on the function and quality of citations[J]. Social studies of science, 1975, 5(1):86-92.
[33] GARZONE M, MERCER R E. Towards an automated citation classifier[J]. Lecture notes in computer science, 2000, 1822:337-346
[34] SPIEGEL-RÖSING I. Science studies:bibliometric and content analysis[J]. Social studies of science, 1977, 7(1):97-113.
[35] OPPENHEIM C, RENN S P. Highly cited old papers and the reasons why they continue to be cited[J]. Journal of the American Society for Information Science, 1978, 29(5):225-231.
[36] RADOULOV R. Exploring automatic citation classification[D]. Waterloo, ON, Canada:University of Waterloo, 2008:33-37.
[37] 陆伟,孟睿,刘兴帮.面向引用关系的引文内容标注框架研究[J].中国图书馆学报,2014,40(6):93-104.
[38] 刘杰,秦春秀,赵捧未,等.基于知识元的科技文本资源内容组织方法[J].情报理论与实践,2018,41(4):128-133.
[39] SHERWIN B. N. How we eie:reflections of life's final vhapter, New Edition[M]. New York:Vintage Books,1995:89.
[40] MONOD J. A biologist's world view(Book Reviews:Chance and Necessity. An essay on the natural philosophy of modern biology)[J]. Science, 1972, 175(4017):49-50.
[41] DENNETT D C. Consciousness explained[M]. New York:Little, Brown and Company, 1991.
[42] VOOS H, DAGAEV K S. Are all citations equal? Or, did we Op. Cit. your idem?[J]. Journal of academic librarianship, 1976, 1.
[43] TEUFEL S, SIDDHARTHAN A, DAN T. Automatic classification of citation function[C]//Proc. 2006 conference on empirical methods in natural language processing. Stroudsburg:Association for Computational Linguistics, 2006:103-110.
[44] LIPETZ B A. Improvement of the selectivity of citation indexes to science literature through inclusion of citation relationship indicators[J]. Journal of the Association for Information Science & Technology, 2014, 16(2):81-90.
[45] HERLACH G. Can retrieval of information from citation indexes be simplified? Multiple mention of a reference as a characteristic of the link between cited and citing article[J]. Journal of the Association for Information Science & Technology, 2014, 29(6):308-310.
[46] ZHU X, TURNEY P, LEMIRE D, et al. Measuring academic influence:Not all citations are equal[J]. Journal of the Association for Information Science & Technology, 2015, 66(2):408-427.
[47] 常思敏.科技论文中冗余参考文献分析[J].出版科学,2015,23(1):43-45.
[48] MACROBERTS M H, MACROBERTS B R. Quantitative measures of communication in science:a study of the formal level[J]. Social studies of science, 1986, 16(1):151-172.
[49] CHUBIN D E, MOITRA S D. Content analysis of references:adjunct or alternative to citation counting?[J]. Social studies of science, 1975, 5(4):423-441.
[50] 刘盛博,丁堃,张春博.基于引用内容性质的引文评价研究[J].情报理论与实践,2015,38(3):77-81.
[51] HASSAN S U, SAFDER I, AKRAM A, et al. A novel machine-learning approach to measuring scientific knowledge flows using citation context analysis[J]. Scientometrics, 2018, 116(4):1-24.
[52] 福柯.知识考古学[M]. 谢强, 马月,译.北京:三联书店,1998:202-215.
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