Research on Transferable Patent Recognition Based on Machine Learning - Details

Author：

Hu, Yifei (Hu, Yifei.) | Yang, Shiwei (Yang, Shiwei.) | Shi, Anjie (Shi, Anjie.)

Indexed by：

EI Scopus

Abstract：

The　construction　of　a　transferable　patent　recognition　model　is　of　great　significance　for　increasing　patent　transformation.　To　construct　the　index　system　affecting　patent　transformation,　this　paper　adds　cross-border　dimension　index　to　the　existing　three-dimensional　patent　value　evaluation　index.　The　results　show　that　the　recognition　accuracy　of　Gradient　boosting　decision　tree　and　Random　forest　is　as　high　as　85.92%,　which　indicates　that　machine　learning　method　can　support　transferable　patent　recognition　in　massive　data.　©　2021　ACM.

Keyword：

Random forests Decision trees Adaptive boosting Patents and inventions Machine learning

Author Community：

[ 1 ] [Hu, Yifei]Beijing University of Technology, China
[ 2 ] [Yang, Shiwei]Beijing University of Technology, China
[ 3 ] [Shi, Anjie]Beijing University of Technology, China

Reprint Author's Address：

Email：

Show more details

Related Keywords：

Malicious email detection via machine learning approaches
2021，2021 International Conference on Electronic Information Engineering and Computer Technology, EIECT 2021
Industrial intelligent forecast of TFT-LCD based on R-SVM
2019，2019 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2019
A High-Dimensional and Multi-granularity Feature Selection Method Based on CNN and RF
2020，15th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2019, co-located with the 5th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2019
Depression Detection and Recognition Research Based on Audio Analysis and Artificial Intelligence Algorithms
2024，1st IEEE International Workshop on Future Intelligent Technologies for Young Researchers, FITYR 2024

Source ：

Year： 2021

Page： 273-278

Language： English

Cited Count：

WoS CC Cited Count： 0

SCOPUS Cited Count：

ESI Highly Cited Papers on the List： 0 Unfold All

WanFang Cited Count：

Chinese Cited Count：

30 Days PV： 7

Affiliated Colleges：

Get Fulltext

DOI Library Discovery Baidu Scholar Search Engineering Village

Type
Departments

All Years Choose Year From to