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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (1): 55-63    DOI: 10.11925/infotech.2096-3467.2017.01.07
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Analyzing Emerging Issues with Technology Entropy Method Based on Patents: Case Study of Carbon Capture
Hou Jianhua(), Guo Shuang
Research Center of Science Technology and Society, Dalian University, Dalian 116622, China
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[Objective]This paper proposes a patent-based technology entropy analysis method, aiming to effectively monitor the development of emerging issues from the patent data. [Methods] First, we built a multi-dimensional technology entropy model for the patent-based system. Second, we analyzed the carbon capture technology from the macro and micro perspectives. [Results] We found that the technology of carbon capture in China was at the crucial development stage. Most of the studies were conducted by universities, which focused on materials with absorption and adsorption abilities. [Limitations] The data collection method needed to be modified to remove the irrelevant ones. [Conclusions] Technology entropy method could effectively analyze the evolution trends of technologies. It provides a feasible tool for us to manage and evaluate the evolution and prediction of new technologies.

Key wordsTechnology Entropy      Patent-based Models      Technology Monitoring      Carbon Capture     
Received: 29 May 2016      Published: 22 February 2017
ZTFLH:  G350  

Cite this article:

Hou Jianhua,Guo Shuang. Analyzing Emerging Issues with Technology Entropy Method Based on Patents: Case Study of Carbon Capture. Data Analysis and Knowledge Discovery, 2017, 1(1): 55-63.

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[1] Porter A L, Jin X Y, Gilmour J E, et al.Technology Opportunities Analysis: Integrating Technology Monitoring, Forecasting and Assessment with Strategic Planning[J]. Society of Research Administrators Journal, 1994, 26(2): 21-31.
[2] Jun S, Park S S, Jang D S.Technology Forecasting Using Matrix Map and Patent Clustering[J]. Industrial Management & Data Systems, 2012, 112(5): 786-807.
doi: 10.1108/02635571211232352
[3] 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.
doi: 10.1007/s11192-011-0457-z
[4] Érdi P, Makovi K, Somogyvári Z, et al.Prediction of Emerging Technologies Based on Analysis of the US Patent Citation Network[J]. Scientometrics, 2013, 95(1): 225-242.
doi: 10.1007/s11192-012-0796-4
[5] 赵焕芳, 朱东华. 信息可视化在技术监测中的应用[J]. 情报杂志, 2005, 24(12): 46-48.
doi: 10.3969/j.issn.1002-1965.2005.12.018
[5] (Zhao Huanfang, Zhu Donghua.Application of Information Visualization in Technology Monitoring[J]. Journal of Intelligence, 2005, 24(12): 46-48.)
doi: 10.3969/j.issn.1002-1965.2005.12.018
[6] 吕一博, 康宇航. 基于共现分析的科技监测地图绘制及实证研究[J]. 科学学研究, 2010, 28(10): 1459-1466.
[6] (Lv Yibo, Kang Yuhang.Mapping and Empirical Study of Science and Technology Monitoring Map Based on Co-occurrence Analysis[J]. Studies in Science of Science, 2010, 28(10): 1459-1466.)
[7] 孙涛涛, 唐小利. 专利文献中的技术热点监测方法及其应用研究[J]. 医学信息学杂志, 2011, 32(10): 40-44.
doi: 10.3969/j.issn.1673-6036.2011.10.011
[7] (Sun Taotao, Tang Xiaoli.Research on Method and Application of Technical Fronts Monitoring in Patent Literature[J]. Journal of Medical Informatics, 2011, 32(10): 40-44.)
doi: 10.3969/j.issn.1673-6036.2011.10.011
[8] 黄鲁成, 石媛嫄, 吴菲菲. 基于专利引用的技术轨道动态分析——以太阳能电池为例[J]. 科学学研究, 2013, 31(3): 358-367.
doi: 10.3969/j.issn.1003-2053.2013.03.006
[8] (Huang Lucheng, Shi Yuanyuan, Wu Feifei.Dynamic Analysis of Identification of Technological Trajectory Based on Patent Citation Network: Taking Solar Cell Technology as an Example[J]. Studies in Science of Science, 2013, 31(3): 358-367.)
doi: 10.3969/j.issn.1003-2053.2013.03.006
[9] Chang P L, Wu C C, Leu H J.Using Patent Analyses to Monitor the Technological Trends in an Emerging Field of Technology: A Case of Carbon Nanotube Field Emission Display[J]. Scientometrics, 2010, 82(1): 5-19.
doi: 10.1007/s11192-009-0033-y
[10] Breitzman A, Thomas P.The Emerging Cluster Model: A Tool for Identifying Emerging Technologies Across Multiple Patent Systems[J]. Research Policy, 2015, 44(1): 195-205.
doi: 10.1007/978-3-319-13018-7_10
[11] 旷景明, 胡奕, 李蓓, 等. 基于生成式拓扑映射的专利空白挖掘技术[J]. 情报理论与实践, 2015, 38(12): 133-136, 142.
doi: 10.16353/j.cnki.1000-7490.2015.12.027
[11] (Kuang Jingming, Hu Yi, Li Bei, et al.Patent Blank Mining Technology Based on Generating Topological Mapping[J]. Information Studies: Theory&Application, 2015, 38(12): 133-136, 142.)
doi: 10.16353/j.cnki.1000-7490.2015.12.027
[12] 任智军, 乔晓东, 徐硕, 等. 基于数据挖掘的技术机会发现模型研究[J]. 情报杂志, 2015, 34(6): 174-177, 190.
doi: 10.3969/j.issn.1002-1965.2015.06.031
[12] (Ren Zhijun, Qiao Xiaodong, Xu Shuo, et al.An Approach for Technology Opportunities Discovery Model Based on Data Mining[J]. Journal of Intelligence, 2015, 34(6): 174-177, 190.)
doi: 10.3969/j.issn.1002-1965.2015.06.031
[13] 翟东升, 夏军, 张杰, 等. 基于专利新兴技术弱信号识别方法研究[J]. 情报杂志, 2015, 34(8): 31-36.
doi: 10.3969/j.issn.1002-1965.2015.08.007
[13] (Zhai Dongsheng, Xia Jun, Zhang Jie, et al.Research on Weak Signal Identification Method of Emerging Technology Based on Patent[J]. Journal of Intelligence, 2015, 34(8): 31-36.)
doi: 10.3969/j.issn.1002-1965.2015.08.007
[14] 朱东华, 袁军鹏. 技术监测指标研究及其实证分析[J]. 科学学研究, 2003, 21(4): 419-422.
doi: 10.3969/j.issn.1003-2053.2003.04.017
[14] (Zhu Donghua, Yuan Junpeng.Research and Empirical Analysis of Technical Monitoring Index[J]. Studies in Science of Science, 2003, 21(4): 419-422.)
doi: 10.3969/j.issn.1003-2053.2003.04.017
[15] Shannon C E.A Mathematical Theory of Communication[J]. Bell System Technology Journal, 1948, 27(3): 379-423.
[16] Jaynes E T.Information Theory and Statistical Mechanics[J]. Physical Review, 1957, 106(4): 620-630.
[17] Bekenstein J D.Black Holes and Entropy[J]. Physical Review D, 1973, 7(8): 2333-2346.
[18] 任佩瑜, 张莉, 宋勇. 基于复杂性科学的管理熵、管理耗散结构理论及其在企业组织与决策中的作用[J]. 管理世界, 2001(6): 142-147.
doi: 10.1038/
[18] (Ren Peiyu, Zhang Li, Song Yong.Management Entropy and Management Dissipative Structure Theory Based on Complexity Science and Its Role in the Organization and Decision Making of Enterprises[J]. Management World, 2001(6): 142-147.)
doi: 10.1038/
[19] 王恒君. 经济能·经济熵·经济危机[J]. 数量经济技术经济研究, 2002 (2): 72-75.
[19] (Wang Hengjun. Economic Energy, Economic Entropy, Economic Crisis[J]. Quantitative & Technical Economics, 2002 (2): 72-75.)
[20] 仲平, 彭斯震, 贾莉, 等. 中国碳捕集、利用与封存技术研发与示范[J]. 中国人口·资源与环境, 2011, 21(12): 41-45.
doi: 10.3969/j.issn.1002-2104.2011.12.007
[20] (Zhong Ping, Peng Sizhen, Jia Li, et al.Development of Carbon Capture, Utilization and Storage (CCUS) Technology in China[J]. China Population, Resources and Environment, 2011, 21(12): 41-45.)
doi: 10.3969/j.issn.1002-2104.2011.12.007
[21] 张卫东, 张栋, 田克忠. 碳捕集与封存技术的现状与未来[J]. 中外能源, 2009, 14(11): 7-14.
[21] (Zhang Weidong, Zhang Dong, Tian Kezhong.Carbon Capture and Sequestration Technology[J]. Sino-Global Energy, 2009, 14(11): 7-14.)
[22] 甘志霞, 刘学之, 尚玥佟. 我国发展二氧化碳捕集与封存技术的挑战及对策建议[J]. 中国科技论坛, 2012(4): 135-138.
doi: 10.3969/j.issn.1002-6711.2012.04.026
[22] (Gan Zhixia, Liu Xuezhi, Shang Yuetong.The Challenge and Suggestion of Developing CCS Technology in China[J]. Forum on Science and Technology in China, 2012(4): 135-138.)
doi: 10.3969/j.issn.1002-6711.2012.04.026
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