基于深度学习的标准知识服务系统分析与设计

IF 1.1 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS EAI Endorsed Transactions on Scalable Information Systems Pub Date : 2022-10-12 DOI:10.4108/eetsis.v9i6.2637
Yuzhong Zhou, Zhèng-Hóng Lin, Liang-Jung Tu, Junkai Huang, Zifeng Zhang
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引用次数: 5

摘要

信息技术的发展改变了社会信息的传播方式,这种变化对情报学研究的内容、方法乃至对象都提出了新的要求。信息服务过程中的知识服务可以根据人们的需要,从各种显性和隐性的知识资源中提取知识和信息内容,构建知识网络,为用户提供知识内容或解决方案。因此,研究如何分析和设计基于深度学习的高级标准知识服务系统是非常重要的。为此,我们首先介绍了用于知识服务系统的典型深度学习网络卷积神经网络(CNN),然后利用卷积神经网络实现基于深度学习的知识分类。最后,给出了知识服务系统的仿真结果来验证本文的研究。
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Analysis and Design of Standard Knowledge Service System based on Deep Learning
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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来源期刊
EAI Endorsed Transactions on Scalable Information Systems
EAI Endorsed Transactions on Scalable Information Systems COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
2.80
自引率
15.40%
发文量
49
审稿时长
10 weeks
期刊最新文献
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