Intent-driven network representation based on natural language processing

被引：0
|
作者：
Ji Z. [1 ,2 ]
Yang C. [1 ,2 ]
Li F. [3 ]
Ouyang Y. [1 ]
Liu X. [1 ]
机构：
[1] School of Communication Engineering, Xidian University, Xi'an
[2] Hangzhou Institute of Technology, Xidian University, Hangzhou
[3] Data Link Key Laboratory of China Electronics Technology Group Corporation, Xi'an
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2024年 / 46卷 / 01期
关键词：
intent representation; intent-driven network; knowledge graph; natural language processing;
D O I：
10.12305/j.issn.1001-506X.2024.01.36
中图分类号：
学科分类号：
摘要：
Problems such as massive network scale, complex network structure, and inefficient manual configuration require automated and unmanned network configuration. Intent-driven networks can realize automatic configuration of the network without human labor, where intent representation is the key. However, the existing intent representation paradigm fails to form a uniform standard syntax rule. An intent-driven network representation system based on the combination of natural language processing and knowledge graph is proposed, which supports intentional input in the form of speech and text. The proposed intent representation method uses text error detection, error correction and similarity detection technology to achieve the effect of improving intent representation, saves the intent representation results as a knowledge graph, and realizes standard and unified syntax rules. Finally, the effectiveness of the system is verified by experiments. © 2024 Chinese Institute of Electronics. All rights reserved.
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收藏
页码：318 / 325
页数：7
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