[1] 刘安蓉, 李莉, 曹晓阳, 等. 颠覆性技术概念的战略内涵及政策启示[J]. 中国工程科学, 2018, 20(6): 7-13. (LIU A R, LI L, CAO X Y, et al. Strategic connotation and policy implications of disruptive technology concepts[J]. Chinese engineering science, 2018, 20(6): 7-13.)
[2] 王康, 陈悦, 王玉奇, 等. 基于专利引用变化的颠覆性技术识别研究[J]. 情报杂志, 2022, 41(1): 74-80. (WANG K, CHEN Y, WANG Y Q, et al. Research on the identification of disruptive technologies based on changes in patent citations[J]. Journal of intelligence, 2022, 41(1): 74-80.)
[3] ANSOFF H I. Managing strategic surprise by response to weak signals[J]. California management review, 1975, 18(2): 21-33.
[4] YOON J. Detecting weak signals for long-term business opportunities using text mining of web news[J]. Expert systems with applications, 2012, 39(16): 12543-12550.
[5] PARK C, CHO S. Future sign detection in smart grids through text mining[J]. Energy procedia, 2017, 128: 79-85.
[6] LEE Y J, PARK J Y. Identification of future signal based on the quantitative and qualitative text mining: a case study on ethical issues in artificial intelligence[J]. Quality & quantity, 2018, 52(2): 653-667.
[7] EBADI A, AUGER A, GAUTHIER Y. Detecting emerging technologies and their evolution using deep learning and weak signal analysis[J]. Journal of informetrics, 2022, 16(4): 5-8.
[8] KIM S, KIM Y E, BAE K J, et al. NEST: A quantitative model for detecting emerging trends using a global monitoring expert network and Bayesian network[J]. Futures, 2013, 52: 59-73.
[9] IRIMIA A, PUNGUTA P, GHEORGHIU R. Tacit knowledge - weak signal detection[EB/OL]. [2025-03-24]. http://www.lrec-conf.org/workshops/lrec2018/W13/pdf/11_W13.pdf.
[10] THORLEUCHTER D, SCHEJA T, VAN DEN POEL D. Semantic weak signal tracing[J]. Expert systems with applications, 2014, 41(11): 5009-5016.
[11] 于光辉, 宁钟, 李昊夫. 基于专利和Bass模型的颠覆性技术识别方法研究[J]. 科学学研究, 2021, 39(8): 1467-1473. (YU G H, NING Z, LI H F. Research on identification method of disruptive technology based on patent and Bass model[J]. Studies in science of science, 2021, 39(8): 1467-1473.)
[12] CHENG Y, HUANG L, RAMLOGAN R, et al. Forecasting of potential impacts of disruptive technology in promising technological areas: elaborating the SIRS epidemic model in RFID technology[J]. Technological forecasting and social change, 2017, 117: 170-183.
[13] 纪亚琨, 余翔, 张奔, 等. 专利网络视角下的潜在颠覆性技术识别——以自动驾驶领域为例[J]. 情报杂志, 2022, 41(12): 46-50. (JI Y K, YU X, ZHANG B, et al. Identifying potentially disruptive technologies from the perspective of patent networks: the field of self-driving vehicles as an example [J]. Journal of intelligence, 2022, 41(12): 46-50.)
[14] 陈育新, 李健, 韩毅. 核心—边缘理论视角下的颠覆性技术识别研究[J]. 情报理论与实践, 2022, 45(8): 121-129. (CHEN Y X, LI J, HAN Y. Research on a method to identify disruptive technologies in the view of core-periphery theory [J]. Information studies: theory & application, 2022, 45(8): 121-129.)
[15] 谭晓, 西桂权, 苏娜, 等. 科学—技术—项目联动视角下颠覆性技术识别研究[J]. 情报杂志, 2023, 42(2): 82-91. (TAN X, XI G Q, SU N, et al. Disruptive technology identification: from the perspective of science and technology project linkage[J]. Journal of intelligence, 2023, 42(2): 82-91.)
[16] 吕璐成, 赵萍, 姜山, 等. 基于候选技术辅助生成和多源数据评估的颠覆性技术识别方法研究[J]. 情报理论与实践, 2023, 46(6): 136-144. (LV L C, ZHAO P, JIANG S, et al. Research on disruptive technology identification method based on candidate technology aided generation and multi-source data evaluation [J]. Information studies: theory & application, 2023, 46(6): 136-144.)
[17] 苏敬勤, 刘建华, 王智琦, 等. 颠覆性技术的演化轨迹及早期识别——以智能手机等技术为例[J]. 科研管理, 2016, 37(3): 13-20. (SU J Q, LIU J H, WANG Z Q, et al. The evolution trajectory and early identification of disruptive technology by taking smartphones and other technologies as an example [J]. Science research management, 2016, 37(3): 13-20.)
[18] WINNINK J J, TIJSSEN R J W, VAN RAAN A F J. Searching for new breakthroughs in science: How effective are computerised detection algorithms?[J]. Technological forecasting and social change, 2019, 146: 673-686.
[19] 王康, 陈悦. 基于异质性专利的颠覆性技术早期识别研究[J]. 科学学研究, 2022, 41(8): 1364-1375. (WANG K, CHEN Y. Research on early identification of disruptive technologies based on heterogeneous patents [J]. Studies in science of science, 2022, 41(8): 1364-1375.)
[20] 邓建军, 刘安蓉, 曹晓阳, 等. 颠覆性技术早期识别方法框架研究――基于科学端的视角[J]. 中国科学院院刊, 2022, 37(5): 674-684. (DENG J J, LIU A R, CAO X Y, et al. Methodological framework of identifying disruptive technologies on emerging stage: based on science.[J]. Bulletin of Chinese Academy of Sciences, 2022, 37(5): 674-684.)
[21] 陈伟, 王莉晓. 颠覆性技术弱信号识别漏斗模型研究[J]. 图书情报工作, 2024, 68(8): 97-111. (CHEN W, WANG L X. Research on disruptive technology weak signal recognition funnel model[J]. Library and information service, 2024, 68(8): 97-111.)
[22] 吴柯烨, 孙建军, 张力, 等. 弱链接突变视角下的技术机会识别研究[J]. 图书情报工作, 2024, 68(10): 81-96. (WU K Y, SUN J J, ZHANG L, et al. A study of technology opportunity identification based on sudden change of weak ties[J]. Library and information service, 2024, 68(10): 81-96.)
[23] EL AKROUCHI M, BENBRAHIM H, KASSOU I. End-to-end LDA-based automatic weak signal detection in web news[J]. Knowledge-based systems, 2021, 212: 106650.
[24] KIM J, LEE C. Novelty-focused weak signal detection in futuristic data: assessing the rarity and paradigm unrelatedness of signals[J]. Technological forecasting and social change, 2017, 120: 59-76.
[25] 苗红, 郭鑫, 吴菲菲. 产业融合弱信号识别研究——以老年智能家居领域为例[J]. 情报杂志, 2020, 39(11): 54-60. (MIAO H, GUO X, WU F F. Research on weak signal identification of industrial convergence taking the field of elderly smart home as an example [J]. Journal of intelligence, 2020, 39(11): 54-60.)
[26] BLANCO S, LESCA H. Business intelligence: integrating knowledge into the selection of early warning signals[EB/OL]. [2025-03-24]. https://www.researchgate.net/publication/228809446_Business_intelligence_integrating_knowledge_into_the_selection_of_early_warning_signals.
[27] TSENG F M, CHENG A C, PENG Y N. Assessing market penetration combining scenario analysis, Delphi, and the technological substitution model: the case of the OLED TV market[J]. Technological forecasting and social change, 2009, 76(7): 897-909.
[28] ROUSSEAU P, CAMARA D, KOTZINOS D. Weak signal detection and identification in large data sets: a review of methods and applications[EB/OL]. [2025-03-24]. http://dx.doi.org/10.13140/RG.2.2.20808.24327/1.
[29] HILTUNEN E. The future sign and its three dimensions[J]. Futures, 2008, 40(3): 247-260.
[30] PARK C, CHO S. Future sign detection in smart grids through text mining[J]. Energy procedia, 2017(128): 79-85.
[31] KWON L N, PARK J H, MOON Y H, et al. Weak signal detecting of industry convergence using information of products and services of global listed companies-focusing on growth engine industry in South Korea[J]. Journal of open innovation: technology, market, and complexity, 2018, 4(1): 10.
[32] 刘亚辉, 许海云, 武华维, 等. 基于多元弱关系融合的科学突破主题早期识别研究[J]. 情报学报, 2023, 42(1): 19-30. (LIU Y H, XU Y H, WU H W, et al. Scientific breakthrough topics identification in an early stage using multiple weak linkage fusion [J]. Journal of the China Society for Scientific and Technical Information, 2023, 42(1): 19-30.)
[33] KIM S, KIM Y E, BAE K J, et al. NEST: A quantitative model for detecting emerging trends using a global monitoring expert network and Bayesian network[J]. Futures, 2013, 52: 59-73.
[34] 周波, 冷伏海. 技术识别研究进展[J]. 情报学进展, 2022, 14: 315-348. (ZHOU B, LENG F H. The research progress of technology identification [J]. Advances in information science, 2022, 14: 315-348.)
[35] 刘亚辉, 许海云. 突破性创新早期识别与弱信号分析综述[J]. 图书情报工作, 2021, 65(4): 89-101. (LUI Y H, XU Y H. A review of early recognition of breakthrough innovations and the weak signal analysis [J]. Library and information service, 2021, 65(4): 89-101.)
[36] 王秀红, 王欣, 王少凡, 等. 基于SimCSE-LDA和异常检测的颠覆性技术识别方法——以农业机器人为例[J]. 情报理论与实践, 2023, 46(5): 135-143. (WANG X H, WANG X, WANG S F, et al. Disruptive technology identification method based on SimCSE-LDA and anomaly detection: a case study of agricultural robots [J]. Information studies: theory & application, 2023, 46(5): 135-143.)
[37] JOANNY G, PERANI S, EULAERTS O. Detection of disruptive technologies by automated identification of weak signals in technology development[C]//CATALANO G, DARAIO C, GREGORI M, et al. Proceedings of the 17th international conference on scientometrics and Informetrics. Rome: ISSI Society, 2019: 2644-2645.
[38] 刘俊婉, 庞博, 徐硕. 基于弱信号的颠覆性技术早期识别研究[J]. 情报学报, 2023, 42(12): 1395-1411. (LIU J W, PANG B, XU S. Early identification of disruptive technology using weak signals [J]. Journal of the China Society for Scientific and Technical Information, 2023, 42(12): 1395-1411.)
[39] 李曼迪, 苏成, 崔怡雯, 等. 面向颠覆性技术情报采集的网络信息源研究[J]. 情报学报, 2021, 40(12): 1294-1300. (LI M D, SU C, CUI Y W, et al. Information web-sources for intelligence studies on disruptive technology [J]. Journal of the China Society for Scientific and Technical Information, 2021, 40(12): 1294-1300.)
[40] WEI X, CUI X, CHENG N, et al. Zero-shot information extraction via chatting with ChatGPT[EB/OL]. [2025-03-24]. https://arxiv.org/pdf/2302.10205.
[41] GROOTENDORST M. KeyBERT: Minimal keyword extraction with BERT[EB/OL]. [2025-03-24]. https://doi.org/10.5281/zenodo.4461265.
[42] MATHUR A, SUCHITHRA M. Application of abstractive summarization in multiple choice question generation[C]//2022 International conference on computational intelligence and sustainable engineering solutions. Piscataway: IEEE, 2022: 409-413.
[43] KHAN M Q, SHAHID A, UDDIN M I, et al. Impact analysis of keyword extraction using contextual word embedding[EB/OL]. [2025-03-24]. https://peerj.com/articles/cs-967.
[44] CAMPOS R, MANGARAVITE V, PASQUALI A, et al. YAKE! Keyword extraction from single documents using multiple local features[J]. Information sciences, 2020, 509: 257-289.
[45] CAMPOS R, MANGARAVITE V, PASQUALI A, et al. YAKE! Collection-Independent automatic keyword extractor[C]//PASI G, PIWOWARSKI B, AZZOPARDI L, et al. Advances in information retrieval. Cham: Springer international publishing, 2018: 806-810.
[46] CAMPOS R, MANGARAVITE V, PASQUALI A, et al. A text feature based automatic keyword extraction method for single documents[C]//PASI G, PIWOWARSKI B, AZZOPARDI L, et al. Advances in information retrieval. Cham: Springer international publishing, 2018: 684-691.
[47] GROOTENDORST M. BERTopic: neural topic modeling with a class-based TF-IDF procedure[EB/OL]. [2025-03-24]. http://arxiv.org/abs/2203.05794.
[48] COHAN A, FELDMAN S, BELTAGY I, et al. SPECTER: document-level representation learning using citation-informed transformers[EB/OL]. [2025-03-24]. http://arxiv.org/abs/2004.07180.
[49] 苏成, 赵志耘, 赵筱媛, 等. 颠覆性技术新阐释：概念、内涵及特征[J]. 情报学报, 2021, 40(12): 1253-1262. (SU C, ZHAO Z Y, ZHAO X Y, et al. New explanation on disruptive technology: concept, connotation and features [J]. Journal of the China Society for Scientific and Technical Information, 2021, 40(12): 1253-1262.)
[50] 史双青. 科技论文学术质量评价研究——基于知识基础和作者水平的二维测度[D]. 北京: 中国科学院大学, 2015. (SHI S Q. Research on academic quality evaluation of scientific papers: a two-dimensional measurement based on knowledge base and author level[D]. Beijing: University of Chinese Academy of Sciences, 2015.)
[51] VEUGELERS R, WANG J. Scientific novelty and technological impact[J]. Research policy, 2019, 48(6): 1362-1372.
[52] YAN Y, TIAN S, ZHANG J. The impact of a paper’s new combinations and new components on its citation[J]. Scientometrics, 2020, 122(2): 895-913.
[53] 徐硕, 李静鸿, 安欣. 基于专利术语的颠覆性技术识别及实证研究[J]. 图书情报工作, 2024, 68(2): 62-72. (XU S, LI J H, AN X. Disruptive technology identification and empirical study on the basis of patent terms [J]. Library and information service, 2024, 68(2): 62-72.)
[54] FUNK R J, OWEN-SMITH J. A dynamic network measure of technological change[J]. Management science, 2017, 63(3): 791-817.
[55] 中国计算机学会. CCF推荐国际学术刊物目录[EB/OL]. [2025-03-24]. https://www.ccf.org.cn/Academic_Evaluation/By_category/. (China Computer Federation. CCF recommended list of international academic journals [EB/OL]. [2025-03-24]. https://www.ccf.org.cn/Academic_Evaluation/By_category/.)
[56] TANG J, ZHANG J, YAO L, et al. Extraction and mining of an academic social network[C] //HUAI J, CHEN R, HON H W, et al. Proceedings of the 17th international conference on World Wide Web. New York: ACM, 2008: 1193-1194.
[57] 贝斐峰, 华昉. 6G时代太赫兹应用前景探讨[J]. 通信企业管理, 2021(3): 75-80. (BEI F F, HUA F. Discussion on the prospects of terahertz application in the 6G era[J]. C-enterprise management, 2021(3): 75-80.)
[58] 李锟, 曹荣荣, 孙毅, 等. 基于忆阻器的感存算一体技术研究进展[J]. 微纳电子与智能制造, 2019, 1(4): 87-102. (LI K, CAO R R, SUN Y, et al. Research progress on the fused technology of sensing, storage and computing based on memristor [J]. Micro/nano electronics and intelligent manufacturing, 2019, 1(4): 87-102.)
