Please wait a minute...
Data Analysis and Knowledge Discovery  2019, Vol. 3 Issue (2): 52-64    DOI: 10.11925/infotech.2096-3467.2017.1319
Current Issue | Archive | Adv Search |
Patent Technology Analysis of Microalgae Biofuel Industrial Chain Based on Topic Model
Jie Zhang,Junbo Zhao(),Dongsheng Zhai,Ningning Sun
Economics and Management School, Beijing University of Technology, Beijing 100124, China
Download: PDF (1498 KB)   HTML ( 11 ) 
Export: BibTeX | EndNote (RIS)      
Abstract  

[Objective] This paper analyzes microalgae biofuel industrial chain technology and the technology inheritance based on topic model, aiming at promoting technological innovations of this industry in China. [Methods] Firstly, we construct the microalgae biofuel industrial chain model, and build the mapping relationship between the industrial chain, technical topics and patents based on the improved LDA topic method. Then, we discover the R&D subjects and analyze technology development trend. Finally, to draw the patent development map under industrial chain segments, the patent-weighted citation network based on semantic similarity is constructed. [Results] In the aspect of algorithm, this paper achieves more accurate topic identification by the improved LDA method. It also find out the development trend of the microalgae biofuel industrial chain technology, and the technical inheritance of industrial chain segments. [Limitations] This paper only focus on the microalgae biofuel industrial chain technology, and a certain degree of background knowledge on the object industry for researchers is necessary when these models as well as results are applied to other industries. [Conclusions] It identifies the key technical segments and hot spots of microalgae biofuel industry chain, and shows that the achievement of technological innovations in this field needs the coordination of more than one segments.
Key words： Microalgae Biofuel      Industrial Chain      LDA Topic Model      Patent     
Received: 25 December 2017      Published: 27 March 2019
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
Jie Zhang
Junbo Zhao
Dongsheng Zhai
Ningning Sun

Cite this article:

Jie Zhang,Junbo Zhao,Dongsheng Zhai,Ningning Sun. Patent Technology Analysis of Microalgae Biofuel Industrial Chain Based on Topic Model. Data Analysis and Knowledge Discovery, 2019, 3(2): 52-64.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.1319     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2019/V3/I2/52

[1] Kim G, Park S, Jang D.Technology Analysis from Patent Data Using Latent Dirichlet Allocation[A]// Lee K M, Park S J, Lee J H. Soft Computing in Big Data Processing[M]. Springer International Publishing, 2014: 71-80.
[2] Venugopalan S, Rai V.Topic Based Classification and Pattern Identification in Patents[J]. Technological Forecasting & Social Change, 2015, 94: 236-250.
[3] 廖列法, 勒孚刚, 朱亚兰. LDA模型在专利文本分类中的应用[J]. 现代情报, 2017, 37(3): 35-39.
[3] (Liao Liefa, Le Fugang, Zhu Yalan.The Application of LDA Model in Patent Text Classification[J]. Journal of Modern Information, 2017, 37(3): 35-39.)
[4] Chen H, Zhang Y, Zhu D.Identifying Technological Topic Changes in Patent Claims Using Topic Modeling[A]// Daim T U, Chiavetta D, Porter A L, et al. Anticipating Future Innovation Pathways Through Large Data Analysis[M]. Springer International Publishing, 2016: 187-209.
[5] Kaplan S, Vakili K, Novelty V S.Usefulness in Innovative Breakthroughs: A Test Using Topic Modeling of Nanotechnology Patents[J]. Strategic Management Journal, 2015, 36: 1435-1457.
[6] 贾龙飞. 专利文献主题发现方法的比较研究——以汽车零部件领域为例[D]. 大连: 大连理工大学, 2014.
[6] (Jia Longfei.Comparative Research of Topic Discovery Methods in Patents Documents——Study on the Case of Auto Parts[D]. Dalian: Dalian University of Technology, 2014.)
[7] 郑学益. 构筑产业链形成核心竞争力—兼谈福建发展的定位及其战略选择[J]. 开放潮, 2000(8): 14-15.
[7] (Zheng Xueyi. Constructing Industry Chains, Forming Core Competence - and Discussing the Positioning of Fujian’s Development and Its Strategic Choice[J]. Open at Tide, 2000(8): 14-15.)
[8] 刘立, 王博. 基于专利情报分析的数控机床产业研究[J]. 科技管理研究, 2010, 30(15): 149-152.
[8] (Liu Li, Wang Bo.Analysis of CNC Machine Industry Based on Patent Intelligence[J]. Science and Technology Management Research, 2010, 30(15): 149-152.)
[9] 吴菲菲, 张亚茹, 黄鲁成, 等. 基于AToT模型的技术主题多维动态演化分析——以石墨烯技术为例[J]. 图书情报工作, 2017, 61(5): 95-102.
[9] (Wu Feifei, Zhang Yaru, Huang Lucheng, et al.Multi-dimension Dynamic Evolution Analysis of Technology Topics Based on AToT by Taking Grapheme Technology as an Example[J]. Library and Information Service. 2017, 61(5): 95-102.)
[10] 陈芳, 郑菲, 彭皓, 等. 基于产业链的产业技术分析方法研究——以食品产业技术分析为例[J]. 图书情报工作, 2013, 57(18): 31-37.
[10] (Chen Fang, Zheng Fei, Peng Hao, et al.Research on Industry and Technology Analysis Method Based on Industry Chain Mapping: Taking Food Industry Analysis for Example[J]. Library and Information Service, 2013, 57(18): 31-37.)
[11] Conte M, Iacobazzi A, Ronchetti M, et al.Hydrogen Economy for a Sustainable Development: State-of-the-Art and Technological Perspectives[J]. Journal of Power Sources, 2001, 100(1): 171-187.
[12] Yasunaga Y, Watanabe M, Korenaga M.Application of Technology Roadmaps to Governmental Innovation Policy for Promoting Technology Convergence[J]. Technological Forecasting and Social Change, 2009, 76(1): 61-79.
[13] Mata T M, Martins A A, Caetano N S.Microalgae for Biodiesel Production and Other Applications: A Review[J]. Renewable and Sustainable Energy Reviews, 2010, 14(1): 217-232.
[14] Singh J, Gu S.Commercialization Potential of Microalgae for Biofuels Production[J]. Renewable and Sustainable Energy Reviews, 2010, 14(9): 2596-2610.
[15] Kumar S P J, Kumar G V, Dash A, et al. Sustainable Green Solvents and Techniques for Lipid Extraction from Microalgae: A Review[J]. Algal Research, 2017, 21: 138-147.
[16] 刘雪艳, 苏忠亮. 微藻生物燃料的研究进展[J]. 化学与生物工程, 2017, 34(3): 11-14.
[16] (Liu Xueyan, Su Zhongliang.Research Progress on Microalgae Biofuel[J]. Chemistry & Bioengineering, 2017, 34(3): 11-14.)
[17] 王博, 刘盛博, 丁堃, 等. 基于LDA主题模型的专利内容分析方法[J]. 科研管理, 2015(3): 111-117.
[17] (Wang Bo, Liu Shengbo, Ding Kun, et al.Patent Content Analysis Method Based on LDA Topic Model[J]. Science Research Management, 2015(3): 111-117.)
[18] Blei D M, Ng A Y, Jordan M I.Latent Dirichlet Allocation[J]. Journal of Machine Learning Research, 2003, 3: 993-1022.
[19] Newman M.Networks: An Introduction[M]. New York: Oxford University Press, 2010: 345-382.
[20] Hofmann M, Chisholm A.Text Mining and Visualization: Case Studies Using Open-source Tools[M]. CRC Press, 2016: 241-264.
[21] Deza E, Deza M M.Dictionary of Distances[M]. Elsevier Science, 2006: 288-296.
[1] Zhang Le, Leng Jidong, Lv Xueqiang, Cui Zhuo, Wang Lei, You Xindong. RLCPAR: A Rewriting Model for Chinese Patent Abstracts Based on Reinforcement Learning[J]. 数据分析与知识发现, 2021, 5(7): 59-69.
[2] Gao Yilin,Min Chao. Comparing Technology Diffusion Structure of China and the U.S. to Countries Along the Belt and Road[J]. 数据分析与知识发现, 2021, 5(6): 80-92.
[3] Lv Xueqiang,Luo Yixiong,Li Jiaquan,You Xindong. Review of Studies on Detecting Chinese Patent Infringements[J]. 数据分析与知识发现, 2021, 5(3): 60-68.
[4] Chen Hao, Zhang Mengyi, Cheng Xiufeng. Identifying Cross-Region Patent Collaboration Opportunities Using LDA and Decision Trees——Case Study of Universities from Guangdong and Wuhan[J]. 数据分析与知识发现, 2021, 5(10): 37-50.
[5] Guan Peng,Wang Yuefen,Jin Jialin,Fu Zhu. Developments of Tech-Innovation Network for Patent Cooperation: Case Study of Speech Recognition in China[J]. 数据分析与知识发现, 2021, 5(1): 112-127.
[6] Hu Yongjun,Wei Tingting,Dou Zixin,Huang Yunyin,Liang Ruicheng,Chang Huiyou. Tech-Development Path of Knife-Scissor Industry in Guangdong with TRIZ Analysis of Patents[J]. 数据分析与知识发现, 2020, 4(2/3): 101-109.
[7] Zhang Jinzhu,Zhu Lipeng,Liu Jingjie. Unsupervised Cross-Language Model for Patent Recommendation Based on Representation[J]. 数据分析与知识发现, 2020, 4(10): 93-103.
[8] Li Jiaquan,Li Baoan,You Xindong,Lü Xueqiang. Computing Similarity of Patent Terms Based on Knowledge Graph[J]. 数据分析与知识发现, 2020, 4(10): 104-112.
[9] Peng Guan,Yuefen Wang. Advances in Patent Network[J]. 数据分析与知识发现, 2020, 4(1): 26-39.
[10] Yan Yu,Lei Chen,Jinde Jiang,Naixuan Zhao. Measuring Patent Similarity with Word Embedding and Statistical Features[J]. 数据分析与知识发现, 2019, 3(9): 53-59.
[11] Jianhua Hou,Pan Liu. Measuring Tech-Entropy of System Evolution: An Empirical Study of Patents[J]. 数据分析与知识发现, 2019, 3(8): 21-29.
[12] Cheng Zhou,Hongqin Wei. Evaluating and Classifying Patent Values Based on Self-Organizing Maps and Support Vector Machine[J]. 数据分析与知识发现, 2019, 3(5): 117-124.
[13] Jinzhu Zhang,Yiming Hu. Extracting Titles from Scientific References in Patents with Fusion of Representation Learning and Machine Learning[J]. 数据分析与知识发现, 2019, 3(5): 68-76.
[14] Linna Xi,Yongxiang Dou. Examining Reposts of Micro-bloggers with Planned Behavior Theory[J]. 数据分析与知识发现, 2019, 3(2): 13-20.
[15] Jinzhu Zhang,Yue Wang,Yiming Hu. Analyzing Sci-Tech Topics Based on Semantic Representation of Patent References[J]. 数据分析与知识发现, 2019, 3(12): 52-60.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626，82624938   E-mail:jishu@mail.las.ac.cn