Analysis of the Evolutionary Trend of Technical Topics in Patents Based on LDA and HMM: Taking Marine Diesel Engine Technology as an Example
Chen Wei1, Lin Chaoran1, Li Jinqiu1, Yang Zaoli2
1. School of Economics and Management, Harbin Engineering University, Harbin 150001; 2. School of Economics and Management, Beijing University of Technology, Beijing 100124
陈伟, 林超然, 李金秋, 杨早立. 基于LDA-HMM的专利技术主题演化趋势分析——以船用柴油机技术为例[J]. 情报学报, 2018, 37(7): 732-741.
Chen Wei, Lin Chaoran, Li Jinqiu, Yang Zaoli. Analysis of the Evolutionary Trend of Technical Topics in Patents Based on LDA and HMM: Taking Marine Diesel Engine Technology as an Example. 情报学报, 2018, 37(7): 732-741.
[1] Kelly K.What technology wants[M]. Penguin Books, 2010: 71-74. [2] 谢志明, 张媛, 贺正楚, 等. 新能源汽车产业专利趋势分析[J]. 中国软科学, 2015(9): 127-141. [3] 韩震, 沈君, 曲莎莎. RFID技术趋势及竞争态势的专利计量分析[J]. 科研管理, 2013(7): 11-16. [4] 中国科学院综合计划局, 中国科学院国家科学图书馆成都文献情报中心. 中国科学院专利分析报告[R]. 成都: 中国科学院, 2015. [5] 林岩. 基于专利数据的知识计量研究评述[J]. 科技管理研究, 2008(9): 91-93. [6] 余江, 陈凯华. 中国战略性新兴产业的技术创新现状与挑战——基于专利文献计量的角度[J]. 科学学研究, 2012(5): 682-695. [7] 刘云, 刘璐, 闫哲, 等. 基于专利计量的全球碳纳米管领域技术创新特征分析[J]. 科研管理, 2016(S1): 337-345. [8] 刘云, 夏民, 武晓明. 中国最大500家外商投资企业在华专利及影响的计量研究[J]. 预测, 2003(6): 19-23. [9] 丁堃, 曲昭, 张春博. 比较视角下的中美银行专利计量分析和创新对策研究[J]. 科研管理, 2014(9): 138-146. [10] Magri A, Giovannini F, Connan R, et al.Nutrient management from biogas digester effluents: a bibliometric-based analysis of publications and patents[J]. International Journal of Environmental Science and Technology, 2017,14(8): 1739-1756. [11] 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(3): 80-84. [12] Figuerola C, Marco F, Pinto M.Mapping the evolution of library and information science (1978-2014) using topic modeling on lisa[J]. Scientometrics, 2017,112(3): 1507-1535. [13] Hu B B, Dong X L, Zhang C W, et al.A lead-lag analysis of the topic evolution patterns for preprints and publications[J]. Journal of the Association for Information Science and Technology, 2015, 66(12): 2643-2656. [14] Jiang H C, Qiang M S, Lin P.Finding academic concerns of the three gorges project based on a topic modeling approach[J]. Ecological Indicators, 2016, 60: 693-701. [15] Li W W.Application of grey prediction theory to forecast technology input within the Chinese high-tech industries[C]// Proceedings of the 3rd International Conference on Advanced Computer Control. IEEE, 2011: 88-92. [16] 李柏洲, 李新. 基于集对分析的企业技术依赖预警及其演化趋势测度[J]. 运筹与管理, 2015, 24(2): 262-271. [17] 黄鲁成, 成雨, 吴菲菲, 等. 关于颠覆性技术识别框架的探索[J]. 科学学研究, 2015, 33(5): 654-664. [18] 李欣, 黄鲁成. 技术路线图方法探索与实践应用研究——基于文献计量和专利分析视角[J]. 科技进步与对策, 2016, 33(5): 62-72. [19] Heo G E, Kang K Y, Song M, et al.Analyzing the field of bioinformatics with the multi-faceted topic modeling technique[J]. BMC Bioinformatics, 2017, 18(Suppl 7): 251. [20] 官建成. 产品创新扩散中的随机现象[J]. 中国管理科学, 1994(3): 44-50. [21] Viterbi A.Viterbi algorithm[M]. John Wiley & Sons, 2003: 6246. [22] Blei D M, Ng A Y, Jordan M I.Latent Dirichlet allocation[J]. Journal of Machine Learning Research, 2003, 3: 993-1022. [23] Blei D.Probabilistic topic models[J]. Communications of the ACM, 2012, 55(4): 77-84. [24] Teh Y W, Jordan M I, Beal M J, et al.Sharing clusters among related groups: hierarchical Dirichlet processes[C]// Proceedings of the Neural Information Processing Systems Conference, 2005: 1385-1392. [25] 关鹏, 王曰芬. 科技情报分析中LDA主题模型最优主题数确定方法研究[J]. 现代图书情报技术, 2016(9): 42-50. [26] Heinrich G. Parameter estimation for text analysis[R/OL]. http:// rakaposhi.eas.asu.edu/f12-cse571-mailarchive/pdflwcW7WccCL. pdf. [27] Welch L.Hidden Markov models and the Baum-welch algorithm[J]. IEEE Information Theory Society Newsletter, 2003, 53(4): 10-13. [28] 刘新华. 中国海洋战略的层次性探析[J]. 中国软科学, 2017(6): 1-13. [29] Hetland M.Network programming[M]// Beginning Python. Springer, 2017: 273-287. [30] AlSumait L, Barbará D, Domeniconi C. On-line LDA: adaptive topic models for mining text streams with applications to topic detection and tracking[C]// Proceedings of the 2008 Eighth IEEE International Conference on Data Mining. Washington, DC: IEEE Computer Society, 2008: 3-12.
