知识图谱构建研究综述

打开文本图片集

中图分类号：TP391 文献标识码：A 文章编号：2096-4706（2025）08-0117-10

Abstract：As a structured semantic knowledge base，the Knowledge Graph plays a key role in many fields such as informationretrval，intellgntquestionasweringandcommendationsystems.Thisapeviews tetheecorecopoents of KnowledgeGraphconstruction，informationextraction，knowledgefusion，andknowledgerasoning.Informationetraction technologyhasdevelopedfromrule-basedmethods toMachineLearing model，andthentoDepLeaingmodel.Itiscurently evolvingtowardsajoint EntityRelationshipExtractionmodel thatreduces erorpropagationandimprovesaccuracy.Inthepart ofknowledgefusion，thestrategiesofentitylinkingandkowledge mergingarediscussed，andtheproblemofentityrecogition is solved byentitydisambiguationand entity alignment.The sectionon knowledge reasoning analyzes the reasoning methods basedonrules，epresentationlearningandDeepLeaming，anditsaplcationinnewknowledge discoveryanderorinformation corection.Finallytehallengesinteonstuctionprocessaepontedout，andsuggestiosforutureesearchditiosare proposed to promote the development of knowledge graph research and application.

Keywords： Knowledge Graph; information extraction; knowledge fusion; knowledge reasoning; Deep Learning

0 引言

20世纪90年代，计算机网络在世界各地得到普及，网络信息资源日渐丰富，信息数据呈现规模海量、类型繁多和快速增长等特征。（剩余24060字）