Research and application of intelligent evaluation method of patent application value of electric power enterprises based on big data mining

Fengshuo Li; Huaming Cao; Lei Wang; Yingtao Li; Jiangang Gong; Guanglei Li

doi:10.1117/12.2661074

16 December 2022 Research and application of intelligent evaluation method of patent application value of electric power enterprises based on big data mining

Fengshuo Li, Huaming Cao, Lei Wang, Yingtao Li, Jiangang Gong, Guanglei Li

Author Affiliations +

Proceedings Volume 12500, Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022); 125004L (2022) https://doi.org/10.1117/12.2661074
Event: 5th International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022), 2022, Chongqing, China

Abstract

The traditional patent value evaluation has problems such as incomplete data and slow processing speed. This paper uses artificial intelligence and big data analysis to quickly screen out patents with high market promotion value from massive patent data. At the same time, combined with the requirements for the transformation and promotion of entrepreneurship and innovation achievements, this paper develops a screening system for entrepreneurship and innovation achievements and patent value based on intelligent analysis of big data, and proposes a hierarchical screening method. Through case analysis, it is applicable to the core patents and ordinary patents of entrepreneurship and innovation achievements. The method proposed in this paper can realize rapid and customizable patent value screening of massive patent data, and can provide new technical means for promoting the level of patent operation.

Citation Download Citation

Fengshuo Li, Huaming Cao, Lei Wang, Yingtao Li, Jiangang Gong, and Guanglei Li "Research and application of intelligent evaluation method of patent application value of electric power enterprises based on big data mining", Proc. SPIE 12500, Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022), 125004L (16 December 2022); https://doi.org/10.1117/12.2661074

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