Analysis and Design of Standard Knowledge Service System based on Deep Learning

Yuzhong Zhou; Zhengping Lin; Liang Tu; Junkai Huang; Zifeng Zhang

doi:10.4108/eetsis.v9i6.2637

Authors

Yuzhong Zhou Electric Power Research Institute, China Southern Power Grid, China
Zhengping Lin Electric Power Research Institute, China Southern Power Grid, China
Liang Tu Electric Power Research Institute, China Southern Power Grid, China
Junkai Huang Electric Power Research Institute of Guizhou Power Grid Co. , Ltd., China
Zifeng Zhang Electric Power Research Institute, China Southern Power Grid, China

DOI:

https://doi.org/10.4108/eetsis.v9i6.2637

Keywords:

Deep learning, standard knowledge service system, knowledge classification, convolution neural network (CNN)

Abstract

The development of information technology has changed the mode of communication of social information, and this change has put forward new requirements on the contents, methods and even objects of information science research. Knowledge service in the information service process can extract knowledge and information content from various explicit and implicit knowledge resources according to people’s needs, build knowledge networks, and provide knowledge content or solutions for users’ problems. Hence, it is very important to investigate how to analyze and design the advanced standard knowledge service system based on deep learning. To this end, we firstly introduce the typical deep learning networks of convolutional neural network (CNN) for the knowledge service system, and then employ the CNN to implement the knowledge classification based on deep learning. Finally, some simulation results on the knowledge service system are presented to validate the proposed studies in this paper.

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