基于自然语言处理的意图驱动网络表征

doi:10.12305/j.issn.1001-506X.2024.01.36

Abstract

Abstract:

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.

Key words: intent-driven network, intent representation, natural language processing, knowledge graph

CLC Number:

TP273+

Zeyang JI, Chungang YANG, Fuqiang LI, Ying OUYANG, Xianglin LIU. Intent-driven network representation based on natural language processing[J]. Systems Engineering and Electronics, 2023, 46(1): 318-325.

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References 30

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现有研究	描述	意图输入形式	意图表征形式
Frenetic^[10]	Frenetic具备有限网络范围和语义, 支持模块的重新设计	高级生命性查询语言	通用网络策略编排库
NDL^[11]	为应用层和网络层提供了通用的语义	RDF	图数据库以RDF保存
Merlin^[12]	使用逻辑谓语、正则表达式和算术公式输入意图, 生成网络策略	声明性程序语言	声明性程序语言
PGA^[13]	将用户意图转化为PGA格式, 实现策略的规范化	类自然语言, 固定参数格式	图结构
Lumi^[5]	使用自然语言处理得到关键信息	自然语言, 人机交互	Nile参数
NLP4^[14]	使用多层感知器将用户意图转化为网络策略	自然语言、语音或文本	P4
[15]	使用自然语言处理对意图进行表征, 如果表征失败, 使用相似度检测对数据库中的意图进行比对	自然语言、语音或文本	知识图谱

意图表征形式	可推理	可复用	可拓展
正则表达式	×	×	×
可拓展标记性语言(extensible markup language, XML)	×	√	√
RDF	√	×	√
知识图谱	√	√	√

源地址	目的地址	业务类型	业务等级	时间
北京A	北京B	数据	普通	2022.9.18
天津C	天津D	语音	重要	2022.10.22
				

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Intent-driven network representation based on natural language processing

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