面向辅助用地报批的知识图谱协同构建与智能问答方法及实现  

Methods and implementation of collaborative construction and intelligent question-answering for knowledge graphs in support of land use approval

作　　者：陈展鹏[1] 杜启勇 胡鑫 杨学习[2] 王天应[1] 江一凡 尹姝彤 邹煜星 CHEN Zhanpeng;DU Qiyong;HU Xin;YANG Xuexi;WANG Tianying;JIANG Yifan;YIN Shutong;ZOU Yuxing(Guangzhou Urban Planning Survey Design&Research Institute Co.,Ltd.,Guangzhou 510060,China;School of Geosciences and Info-physics,Central South University,Changsha 410083,China)

机构地区：[1]广州市城市规划勘测设计研究院有限公司,广州510060 [2]中南大学地球科学与信息物理学院,长沙410083

出　　处：《时空信息学报》2025年第1期94-103,共10页JOURNAL OF SPATIO-TEMPORAL INFORMATION

基　　金：广州市城市规划勘测设计研究院科技发展基金项目(2021科研(院)124)。

摘　　要：持续推进用地报批业务的数字化、智能化建设是夯实自然资源“两统一”工作的重要内容。受制于对报批流程各环节复杂关联关系的认知局限,用地管理过程经常面临业务关联弱、政策查找难等问题,进而影响报批业务的工作效率和成效。本文立足于知识图谱与大语言模型在复杂业务中的技术互补性,提出一种面向辅助用地报批的知识图谱协同构建与智能问答技术框架,实现对用地报批业务知识的系统整合与辅助式问答;并进一步研发设计辅助用地报批智能服务平台;为评价方法的有效性,将服务平台的知识问答功能与百度搜索引擎进行比较分析。结果表明,本服务平台在为用地报批领域提供新型知识组织范式的同时,亦可在辅助决策实践中展现出显著的应用价值。研究成果可为推进用地报批领域治理能力的数字化转型与智能化升级提供可行路径。[Objective]Enhancing the efficiency and effectiveness of the land use approval process through digitalization and intelligent technologies is crucial for consolidating efforts in natural resource management,specifically achieving“dual unification”.This study tackles challenges posed by fragmented data management and the complexity of policy retrieval within the land use approval workflow.By leveraging the ontology of land use approval processes,we have developed a collaborative framework that integrates the construction of a knowledge graph with intelligent question-and-answer(Q&A)capabilities.This framework is designed to support and streamline land use approval activities,providing a robust decision-support tool that addresses issues related to weak business associations and difficult policy access.[Method]The methodological approach involves systematically extracting and integrating information from various data sources relevant to land use policies and approval procedures.Utilizing advanced information extraction techniques and graph construction algorithms,we built a dynamic knowledge graph encapsulating the complex dependencies and regulations governing land use.Additionally,a knowledge retrieval-augmented generation model was developed to facilitate sophisticated Q&A interactions,allowing users to engage with the system via natural language queries and receive accurate,context-aware responses.This integrated framework was implemented within an intelligent service platform tailored for land use approval,and its effectiveness was assessed through a qualitative comparative analysis against traditional search engines,such as Baidu.[Result]The implementation of the proposed framework led to the successful development of an intelligent service platform that significantly enhances the land use approval process.The constructed knowledge graph introduces a novel organizational structure for land use-related information,enabling seamless integration and retrieval of policy data.The intelligent Q&A system outperf

关 键 词：知识图谱 用地报批 图谱构建 信息抽取 大语言模型 智能问答 检索增强生成 辅助决策 

分 类 号：P208[天文地球—地图制图学与地理信息工程]