[1] IARPA. Foresightand understanding from scientific exposition (FUSE)[EB/OL].[2021-11-10]. https://www.iarpa.gov/index.php/research-programs/fuse. [2] SCHIEBEL E, HOERLESBERGER M, ROCHE I, et al. An advanced diffusion model to identify emergent research issues:the case of optoelectronic devices[J]. Scientometrics, 2010, 83(3):765-781. [3] REDING D F, EATON J. Science & technology trends:2020-2040[R]. Brussels:NATO Science & Technology Organization, 2020. [4] 侯剑华,王鹏.国内新兴技术及其管理研究综述[J].科学管理研究, 2012, 30(6):29-32. [5] 周萌,朱相丽.新兴技术概念辨析及其识别方法研究进展[J].情报理论与实践, 2019, 42(10):162-169. [6] 王玏,吴新年.新兴技术识别方法研究综述[J].图书情报工作, 2020, 64(4):125-135. [7] 刘小玲,谭宗颖.新兴技术主题识别方法研究进展[J].图书情报工作, 2020, 64(11):145-152. [8] 徐建国,李孟军,游翰霖.新兴技术识别研究进展[J].情报杂志, 2018, 37(12):8-12, 7. [9] 卢小宾,杨冠灿,徐硕,等.计量与演化视角下的新兴技术识别研究进展评述[J].情报学报, 2020, 39(6):651-661. [10] ROTOLO D, HICKS D, MARTIN B R. What is an emerging technology?[J]. Research policy, 2015, 44(10):1827-1843. [11] DAY G S, SCHOEMAKER P J H. Avoiding the pitfalls of emerging technologies[J]. California management review, 2000, 42(2):8-33. [12] 华宏鸣,郑绍濂.高新技术管理[M].上海:复旦大学出版社, 1995. [13] SMALL H, BOYACK K W, KLAVANS R. Identifying emerging topics in science and technology[J]. Research policy, 2014, 43(8):1450-1467. [14] BREITZMAN A, THOMAS P. The emerging clusters model:a tool for identifying emerging technologies across multiple patent systems[J]. Research policy, 2015, 44(1):195-205. [15] 王凌燕,方曙,季培培.利用专利文献识别新兴技术主题的技术框架研究[J].图书情报工作, 2011, 55(18):74-78, 23. [16] ALEXANDER J, CHASE J, NEWMAN N, et al. Emergence as a conceptual framework for understanding scientific and technological progress[C]//2012 proceedings of PICMET'12:technology management for emerging technologies. New York:IEEE, 2012:1286-1292. [17] PORTER A L, ROESSNER J D, JIN X Y, et al. Measuring national 'emerging technology' capabilities[J]. Science and public policy, 2002, 29(3):189-200. [18] HALAWEH M. Emerging technology:what is it[J]. Journal of technology management & innovation, 2013, 8(3):108-115. [19] COZZENS S, GATCHAIR S, KANG J, et al. Emerging technologies:quantitative identification and measurement[J]. Technology analysis & strategic management, 2010, 22(3):361-376. [20] 李仕明,李平,肖磊.新兴技术变革及其战略资源观[J].管理学报, 2005(3):304-306, 361. [21] 曹艺文,许海云,武华维,等.基于引文曲线拟合的新兴技术主题的突破性预测——以干细胞领域为例[J].图书情报工作, 2020, 64(5):100-113. [22] PORTER A L. Technology futures analysis:toward integration of the field and new methods[J]. Technological forecasting and social change, 2004, 71(3):287-303. [23] 汪雪锋,张硕,韩晓彤,等.技术预测研究现状与未来展望[J].农业图书情报, 2019, 31(6):4-11. [24] 李欣,王静静,杨梓,等.基于SAO结构语义分析的新兴技术识别研究[J].情报杂志, 2016, 35(3):80-84. [25] SMALL H, GRIFFITH B C. The structure of scientific literatures I:identifying and graphing specialties[J]. Science studies, 1974, 4(1):17-40. [26] CHEN C. Citespace II:detecting and visualizing emerging trends and transient patterns in scientific literature[J]. Journal of the American Society for Information Science and Technology, 2006, 57(3):359-377. [27] SMALL H. Tracking and predicting growth areas in science[J]. Scientometrics, 2006, 68(3):595-610. [28] KAJIKAWA Y, YOSHIKAWA J, TAKEDA Y, et al. Tracking emerging technologies in energy research:toward a roadmap for sustainable energy[J]. Technological forecasting and social change, 2008, 75(6):771-782. [29] KAJIKAWA Y, TAKEDA Y. Structure of research on biomass and bio-fuels:a citation-based approach[J]. Technological forecasting and social change, 2008, 75(9):1349-1359. [30] SHIBATA N, KAJIKAWA Y, TAKEDA Y, et al. Detecting emerging research fronts based on topological measures in citation networks of scientific publications[J]. Technovation, 2008, 28(11):758-775. [31] SHIBATA N, KAJIKAWA Y, TAKEDA Y, et al. Detecting emerging research fronts in regenerative medicine by the citation network analysis of scientific publications[J]. Technological forecasting and social change, 2011, 78(2):274-282. [32] ZHOU Y, DONG F, KONG D, et al. Unfolding the convergence process of scientific knowledge for the early identification of emerging technologies[J]. Technological forecasting and social change, 2019, 144:205-220. [33] KUUSI O, MEYER M. Anticipating technological breakthroughs:using bibliographic coupling to explore the nanotubes paradigm[J]. Scientometrics, 2007, 70(3):759-777. [34] 李蓓,陈向东.基于专利引用耦合聚类的纳米领域新兴技术识别[J].情报杂志, 2015, 34(5):35-40. [35] CHO T S, SHIH H Y. Patent citation network analysis of core and emerging technologies in Taiwan:1997-2008[J]. Scientometrics, 2011, 89(3):795-811. [36] HO J C, SAW E C, LU L Y Y, et al. Technological barriers and research trends in fuel cell technologies:a citation network analysis[J]. Technological forecasting and social change, 2014, 82:66-79. [37] ZHANG S, HAN F. Identifying emerging topics in a technological domain[J]. Journal of intelligent & fuzzy systems, 2016, 31(4):2147-2157. [38] XU H, WINNINK J, YUE Z, et al. Multidimensional scientometric indicators for the detection of emerging research topics[J]. Technological forecasting and social change, 2021, 163:120490. [39] SHIBATA N, KAJIKAWA Y, SAKATA I. Extracting the commercialization gap between science and technology-case study of a solar cell[J]. Technological forecasting and social change, 2010, 77(7):1147-1155. [40] OHNIWA R L, HIBINO A. Generating process of emerging topics in the life sciences[J]. Scientometrics, 2019, 121(3):1549-1561. [41] LEE W H. How to identify emerging research fields using scientometrics:an example in the field of information security[J]. Scientometrics, 2008, 76(3):503-525. [42] KIM Y G, SUH J H, PARK S C. Visualization of patent analysis for emerging technology[J]. Expert systems with applications, 2008, 34(3):1804-1812. [43] 方曙,胡正银,庞弘燊,等.基于专利文献的技术演化分析方法研究[J].图书情报工作, 2011, 55(22):42-46. [44] KATSURAI M, ONO S. TrendNets:mapping emerging research trends from dynamic co-word networks via sparse representation[J]. Scientometrics, 2019, 121(3):1583-1598. [45] YOON J, CHOI S, KIM K. Invention property-function network analysis of patents:a case of silicon-based thin film solar cells[J]. Scientometrics, 2011, 86(3):687-703. [46] CHOUDHURY N, FAISAL F, KHUSHI M. Mining temporal evolution of knowledge graphs and genealogical features for literature-based discovery prediction[J]. Journal of informetrics, 2020, 14(3):101057. [47] HUANG L, CHEN X, NI X, et al. Tracking the dynamics of co-word networks for emerging topic identification[J]. Technological forecasting and social change, 2021, 170:120944. [48] 黄鲁成,唐月强,吴菲菲,等.基于文献多属性测度的新兴主题识别方法研究[J].科学学与科学技术管理, 2015, 36(2):34-43. [49] 张维冲,王芳,赵洪.多源信息融合用于新兴技术发展趋势识别——以区块链为例[J].情报学报, 2019, 38(11):1166-1176. [50] 刘俊婉,龙志昕,王菲菲.基于LDA主题模型与链路预测的新兴主题关联机会发现研究[J].数据分析与知识发现, 2019, 3(1):104-117. [51] 黄璐,朱一鹤,张嶷.基于加权网络链路预测的新兴技术主题识别研究[J].情报学报, 2019, 38(4):335-341. [52] DOTSIKA F, WATKINS A. Identifying potentially disruptive trends by means of keyword network analysis[J]. Technological forecasting and social change, 2017, 119:114-127. [53] YOON B, PARK Y. A text-mining-based patent network:analytical tool for high-technology trend[J]. The journal of high technology management research, 2004, 15(1):37-50. [54] FURUKAWA T, MORI K, ARINO K, et al. Identifying the evolutionary process of emerging technologies:a chronological network analysis of World Wide Web conference sessions[J]. Technological forecasting and social change, 2015, 91:280-294. [55] YOON J, KIM K. Identifying rapidly evolving technological trends for R & D planning using SAO-based semantic patent networks[J]. Scientometrics, 2011, 88(1):213-228. [56] 孔德婧,董放,陈子婧,等.离群专利视角下的新兴技术预测——基于BERT模型和深度神经网络[J].图书情报工作, 2021, 65(17):131-141. [57] SONG K, KIM K, LEE S. Identifying promising technologies using patents:a retrospective feature analysis and a prospective needs analysis on outlier patents[J]. Technological forecasting and social change, 2018, 128:118-132. [58] ZHOU Y, DONG F, LIU Y, et al. A deep learning framework to early identify emerging technologies in large-scale outlier patents:an empirical study of CNC machine tool[J]. Scientometrics, 2021, 126(2):969-994. [59] ERDI P, MAKOVI K, SOMOGYVARI Z, et al. Prediction of emerging technologies based on analysis of the US patent citation network[J]. Scientometrics, 2013, 95(1):225-242. [60] 张浩.数据融合视角下技术预测方法研究[D].长春:吉林大学, 2019. [61] 董放,刘宇飞,周源.基于LDA-SVM论文摘要多分类新兴技术预测[J].情报杂志, 2017, 36(7):40-45, 133. [62] 党倩娜,杨倩,刘永千.基于大数据方法的新兴技术新颖性测度[J].图书馆杂志, 2019, 38(4):91-100. [63] 罗建,蔡丽君,史敏.基于专利的两阶段新兴技术识别研究——以图像识别技术为例[J].情报科学, 2019, 37(12):57-62. [64] 宋欣娜,郭颖,席笑文.基于专利文献的多指标新兴技术识别研究[J].情报杂志, 2020, 39(6):76-81, 88. [65] 李静,徐路路,赵素君.基于时间序列分析和SVM模型的基金项目新兴主题趋势预测与可视化研究[J].情报理论与实践, 2019, 42(1):118-123, 152. [66] 李荣,刘静,李梦辉,等.基于基金项目数据的人工智能技术前沿性测度研究——技术创新决策视角分析[J].情报杂志, 2020, 39(9):81-87. [67] 周源,刘宇飞,薛澜.一种基于机器学习的新兴技术识别方法:以机器人技术为例[J].情报学报, 2018, 37(9):939-955. [68] 任智军,乔晓东,张江涛.新兴技术发现模型研究[J].现代图书情报技术, 2016(S1):60-69. [69] 唐恒,邱悦文.多源信息视角下的多指标新兴技术主题识别研究——以智能网联汽车领域为例[J].情报杂志, 2021, 40(3):81-88. [70] 白敬毅,颜端武,陈琼.基于主题模型和曲线拟合的新兴主题趋势预测研究[J].情报理论与实践, 2020, 43(7):130-136, 193. [71] LIU X, PORTER A L. A 3-dimensional analysis for evaluating technology emergence indicators[J]. Scientometrics, 2020, 124(1):27-55.作者贡献说明:刘盼盼:论文框架设计,论文撰写与修改;王丽:提出研究思路,论文修改与完善。 |