现代信息科技2026，Vol.10Issue(10)：101-106,111,7.DOI:10.19850/j.cnki.2096-4706.2026.10.018
基于思维链的低资源电信运维知识图谱构建
CoT-Based Low-resource Knowledge Graph Construction for Telecom Operator's Network Operations and Maintenance
摘要
Abstract
As the scale and service complexity of communication networks continue to grow,the expansion of network fault Knowledge Graphs faces challenges of data scarcity and quality fluctuations.A self-planning and self-verification method for knowledge graph generation based on Chain-of-Thought(CoT)for operation and maintenance scenarios is proposed.This method employs a small amount of high-quality seed data and structured prompts to drive Large Language Models,and utilizes a three-stage generation process of analysis-planning-synthesis.It employs a two-stage quality optimization strategy comprising screening based on synthetic data similarity distribution and correction based on content verification,aimed at automatically identifying and correcting low-quality samples.Experimental validation in low-resource operator scenarios demonstrates that this method effectively filters out semantically irrelevant and redundant samples,significantly enhancing the consistency and accuracy of synthetic data.The model design quality score improves by over 15%compared to the baseline,enabling controllable scalability of the operation and maintenance Knowledge Graph.关键词
合成数据/思维链/大语言模型/运营商网络运维/知识图谱构建Key words
synthetic data/chain-of-thought/Large Language Model/network operation and maintenance of operator/Knowledge Graph construction分类
信息技术与安全科学引用本文复制引用
陈卓,张晓峰,禤晓昭,张佐中,陈光明,杨以术,徐况,金书意,汪盈盈..基于思维链的低资源电信运维知识图谱构建[J].现代信息科技,2026,10(10):101-106,111,7.基金项目
合肥市重大科技攻关"揭榜挂帅"项目(2024SZD005) （2024SZD005）
