整合主题的学科知识网络构建与演化分析框架研究
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摘要
【目的/意义】当前,对学科研究前沿的挖掘和探测成为学科知识创新服务的重要支撑。本文从整合主题的视角出发,提出了学科知识网络构建与演化分析的框架,通过该框架实现学科研究前沿的挖掘和探测。【方法/过程】整合主题的学科知识网络构建与演化分析框架主要包括三个部分。一是,基于主题挖掘与主题语义关联计算相结合的视角,提出了整合主题的学科知识网络构建流程;二是,基于复杂网络结构分析理论提出了整合主题的网络结构演化分析方法,以挖掘和探测前沿主题;三是,基于复杂网络演化建模与多agent系统仿真建模方法,提出了整合主题的学科知识网络演化建模框架,通过演化建模探索学科知识结构的演化机理。【结果/结论】以上整合主题的学科知识网络构建流程和演化分析、演化建模框架,形成了"主题挖掘→网络构建→结构演化→仿真建模"的研究新思路,为学科知识创新服务提供了新的方法与工具。
【Purpose/significance】At present, mining and exploration of research fronts has become an important support for academic knowledge innovation services. From the perspective of integrating topics, this paper proposes a framework for the construction and evolution analysis of discipline knowledge networks. Through this framework, research fronts of discipline could be found. 【Method/process】This paper puts forward the framework from three aspects. First, it proposes the constructing process of discipline knowledge network based on integrating topics, through topic extraction and topic semantic association calculation. Second, it puts forward evaluation analysis method of network structure, by complexity network structure analysis theory. Third, it puts forward frame of network evaluation modeling, based on complexity network evaluation modeling and multi-agent system modeling. 【Result/conclusion】Through the above steps, the paper puts forward a research idea, which follows the line of"topic mining"to"network construction"to"structure evaluation"to"simulation modeling". This frame work can support new methods and tools for knowledge service oriented to discipline knowledge innovation.
【Purpose/significance】At present, mining and exploration of research fronts has become an important support for academic knowledge innovation services. From the perspective of integrating topics, this paper proposes a framework for the construction and evolution analysis of discipline knowledge networks. Through this framework, research fronts of discipline could be found. 【Method/process】This paper puts forward the framework from three aspects. First, it proposes the constructing process of discipline knowledge network based on integrating topics, through topic extraction and topic semantic association calculation. Second, it puts forward evaluation analysis method of network structure, by complexity network structure analysis theory. Third, it puts forward frame of network evaluation modeling, based on complexity network evaluation modeling and multi-agent system modeling. 【Result/conclusion】Through the above steps, the paper puts forward a research idea, which follows the line of"topic mining"to"network construction"to"structure evaluation"to"simulation modeling". This frame work can support new methods and tools for knowledge service oriented to discipline knowledge innovation.
引文
1中国科学院科技战略咨询研究院,中科院文献情报中心,科睿唯安.2017研究前沿[EB/OL].www.useit.com.cn/thr ead-17026-1-1.html,2018-03-25
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14 Robins,G.and M.Alexander.Small Worlds Among Interlocking Directors:Network Structure and Distance in Bipartite Graphs[J].Computational&Mathematical Organization Theory,2004,10(1):69–94.
15 Latapy,Matthieu,Clémence Magnien,and Nathalie Del Vecchio.Basic Notions for the Analysis of Large Two-Mode Networks[J].Social Networks,2008,30(1):31–48.
16 Merler S,Ajelli M.The Role of Population Heterogeneity and Human Mobility in the Spread of Pandemic Influenza[J].Proceedings Biological Sciences,2010,277(1681):557-565.
17 Newman M E J.The Structure of Scientific Collaboration Networks[J].Proceedings of the National Academy of Sciences,2001,98(2):404-409.
18 Watts D J,Strogatz S H.Collective Dynamics of'Small-Wo rld'Networks[J].Nature,1998,393(6684):440-442.
19 Barabási A,Albert R.Emergence of Scaling in Random Networks[J].Science,1999,286(5439):509-512.
20 Cowan R,Jonard N.Network Structure and the Diffusion of Knowledge[J].Journal of Economic Dynamics&Control,2004,28(8):1557-1575.
21 Morone P,Taylor R.Knowledge Diffusion Dynamics and Network Properties of Face-To-Face Interactions[J].Journal of Evolutionary Economics,2004,14(3):327-351.
22 李纲,巴志超.科研合作超网络下的知识扩散演化模型研究[J].情报学报,2017,36(3):274-284.
23 岳增慧,许海云,方曙.基于个体行为的科研合作网络知识扩散建模研究[J].情报学报,2015,34(8):819-832.
24 岳增慧,许海云,方曙.基于微分动力学的科研合作网络知识扩散模型及影响机制研究[J].情报学报,2015,34(11):1132-1142.
25 巴志超,李纲,朱世伟.科研合作网络的知识扩散机理研究[J].中国图书馆学报,2016,42(5):68-84.
26 夏昊翔,王国秀,宣照国,等.针对科研合作网络演化建模的基于Agent实验平台原型[J].情报学报,2010,29(4):634-640.
27 Sun X,Kaur J,Milojevi S,et al.Social Dynamics of Science[J].Scientific Reports,2013,3(1):1069-1079.
2 顾东蕾.论学科知识网络[J].情报杂志,2008,27(9):50-55.
3 张金柱,韩涛,王小梅.复杂网络在图情领域的研究和应用综述[J].情报学报,2012,31(9):907-914.
4 邱均平.利用知识网络深化网络信息计量学研究[J].图书情报工作,2007,51(9):5.
5 赵蓉英,邱均平.知识网络研究(Ⅰ)——知识网络概念演进之探究[J].情报学报,2007(2):198-209.
6 赵蓉英.知识网络研究(Ⅱ)——知识网络的概念、内涵和特征[J].情报学报,2007,26(3):470-476.
7 顾东蕾.基于生物信息学的学科知识网络及其应用研究[D].南京:南京大学,2007.
8 顾东蕾.论学科知识网络的理论基础[J].图书情报工作,2008,52(9):32-35.
9 周晓英.情报学进展系列论文之五知识网络、知识链接和知识服务研究[J].情报资料工作,2010,31(2):6-11.
10 王旻霞,赵丙军.科学知识网络的结构特征及演化动力[J].情报杂志,2014,(5):88-95.
11 Blei D M,Ng A Y,Jordan M I.Latent Dirichlet Allocation[J].Journal of Machine Learning Research,2003,(3):993-1022.
12 汪小帆.复杂网络理论及其应用[M].北京:清华大学出版社,2006:1-60.
13 Saram?ki J,Kivel?M,Onnela J P,et al.Generalizations of the Clustering Coefficient to Weighted Complex Networks[J].Physical Review E Statistical Nonlinear&Soft Matter Physics,2007,75(2 Pt 2):027105.
14 Robins,G.and M.Alexander.Small Worlds Among Interlocking Directors:Network Structure and Distance in Bipartite Graphs[J].Computational&Mathematical Organization Theory,2004,10(1):69–94.
15 Latapy,Matthieu,Clémence Magnien,and Nathalie Del Vecchio.Basic Notions for the Analysis of Large Two-Mode Networks[J].Social Networks,2008,30(1):31–48.
16 Merler S,Ajelli M.The Role of Population Heterogeneity and Human Mobility in the Spread of Pandemic Influenza[J].Proceedings Biological Sciences,2010,277(1681):557-565.
17 Newman M E J.The Structure of Scientific Collaboration Networks[J].Proceedings of the National Academy of Sciences,2001,98(2):404-409.
18 Watts D J,Strogatz S H.Collective Dynamics of'Small-Wo rld'Networks[J].Nature,1998,393(6684):440-442.
19 Barabási A,Albert R.Emergence of Scaling in Random Networks[J].Science,1999,286(5439):509-512.
20 Cowan R,Jonard N.Network Structure and the Diffusion of Knowledge[J].Journal of Economic Dynamics&Control,2004,28(8):1557-1575.
21 Morone P,Taylor R.Knowledge Diffusion Dynamics and Network Properties of Face-To-Face Interactions[J].Journal of Evolutionary Economics,2004,14(3):327-351.
22 李纲,巴志超.科研合作超网络下的知识扩散演化模型研究[J].情报学报,2017,36(3):274-284.
23 岳增慧,许海云,方曙.基于个体行为的科研合作网络知识扩散建模研究[J].情报学报,2015,34(8):819-832.
24 岳增慧,许海云,方曙.基于微分动力学的科研合作网络知识扩散模型及影响机制研究[J].情报学报,2015,34(11):1132-1142.
25 巴志超,李纲,朱世伟.科研合作网络的知识扩散机理研究[J].中国图书馆学报,2016,42(5):68-84.
26 夏昊翔,王国秀,宣照国,等.针对科研合作网络演化建模的基于Agent实验平台原型[J].情报学报,2010,29(4):634-640.
27 Sun X,Kaur J,Milojevi S,et al.Social Dynamics of Science[J].Scientific Reports,2013,3(1):1069-1079.