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Data Analysis and Knowledge Discovery  2019, Vol. 3 Issue (2): 52-64    DOI: 10.11925/infotech.2096-3467.2017.1319
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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
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[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 wordsMicroalgae Biofuel      Industrial Chain      LDA Topic Model      Patent     
Received: 25 December 2017      Published: 27 March 2019

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.

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