[1] 邱均平,李小涛. 基于引文网络挖掘和时序分析的知识扩散研究[J]. 情报理论与实践, 2014(7):5-10.
[2] 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(3):58-68.
[3] 岳增慧,许海云. 学科引证网络知识扩散特征研究[J]. 情报学报, 2019, 38(1):5-16.
[4] NOYONS E C M, RAAN A F J V.Monitoring scientific developments from a dynamic perspective:self-organized structuring to map neural network research[J].Journal of the Association for Information Science & Technology, 1998, 49(1):68-81.
[5] 雷迭斯多夫. 科学计量学的挑战:科学交流的发展、测度和自组织[M].乌云,译. 北京:科学技术文献出版社, 2003.
[6] LEYDESDORFF L, COZZENS S, PETER V D B. Tracking areas of strategic importance using scientometric journal mappings[J]. Research policy, 1994, 23(2):217-229.
[7] LEYDESDORFF L. Statistics for the dynamic analysis of scientometric data:the evolution of the sciences in terms of trajectories and regimes[J]. Scientometrics, 2013, 96(3):731-741.
[8] POPPER K R.The logic of scientific discovery[J]. Yinshan academic journal, 2005,12(11):53-54.
[9] 靖继鹏,马费成,张向. 情报科学理论[M].北京:科学出版社,2009.
[10] 刘则渊. 跨越学术分水岭[M]. 北京:人民出版社,2012.
[11] 万昊. 科学知识规模增长模式研究-基于数学建模和仿真论证[D]. 北京:中国科学院大学,2017.
[12] 刘自强,许海云,罗瑞,等. 基于主题关联分析的科技互动模式识别方法研究[J]. 情报学报, 2019, 38(10):997-1011.
[13] 安宁,滕广青,白淑春,等. 领域知识聚类性的动态演化分析[J]. 图书情报工作, 2018,62(10):85-93.
[14] GIRVAN M, NEWMAN M E J. Community structure in socia1and biological networks[J]. Proceedings of the National Academy of Sciences of the United States of America,2002,99(12):7821-7826.
[15] BETTENCOURT L M A, KAISER D I, KAUR J. Scientific discovery and topological transitions in collaboration networks[J]. Journal of informetrics, 2009, 3(3):210-221.
[16] 白如江,冷伏海.k-clique社区知识创新演化方法研究[J].图书情报工作,2013,57(17):94-99.
[17] 王晓光,程齐凯. 基于NEViewer的学科主题演化可视化分析[J]. 情报学报, 2013, 32(9):900-911.
[18] 滕广青. 基于频度演化的领域知识关联关系涌现[J]. 中国图书馆学报,2018,44(3):79-95.
[19] 滕广青. 关联驱动的领域知识群落生长[J]. 中国图书馆学报, 2017,43(3):58-71.
[20] KUHN T S. The structure of scientific revolutions[M]. Chicago:University of Chicago Press, 1962.
[21] PRICE D J. Science since babylon[M]. New Haven:Yale University Press, 1961.
[22] PRICE D J. Little science, big science[M]. New York:Columbia University Press, 1963.
[23] DIANA C.Invisible colleges-diffusion of knowledge in scientific communities[M]. Chicago:The University of Chicago Press, 1972.
[24] 罗双玲,张文琪,夏昊翔.基于半积累引文网络社区发现的学科领域主题演化分析——以"合作演化"领域为例[J].情报学报,2017,36(1):100-110.
[25] BLONDEL V D,GUILLAUME J L, LAMBIOTTE R, et al. Fast unfolding of communities in large networks[J]. Journal of statistical mechanics:theory and experiment, 2008, 2008(10):10008.
[26] BLONDEL V D. Louvain algorithm[EB/OL].[2019-07-17].https://perso.uclouvain.be/vincent.blondel/research/louvain.html.
[27] NEWMAN M E J, GIRVAN M. Finding and evaluating community structure in networks[J].Physical review, 2004, 69(2):108-113.
[28] 周练.Word2vec的工作原理及应用探究[J].科技情报开发与经济,2015,25(2):145-148.
[29] MIKOLOV T, SUTSKEVER I, CHEN K, et al. Distributed representations of words and phrases and their compositionality[C]//Advances in neural information processing systems 26. Cambridge:Neural Information Processing Systems Foundation Inc., 2013:3111-3119.
[30] GROVER A, LESKOVEC J. Node2vec:scalable feature learning for networks[C]//Proceeding of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining. New York:ACM, 2016:855-864.
[31] LAURENS V D M, HINTON G.Visualizing data using t-SNE[J]. Journal of machine learning research, 2008, 9(11):2579-2605. |