情报学报2023年8月第42卷第8期JournaloftheChinaSocietyforScientificandTechnicalInformation,Aug.2023,42(8):967-979基于RDF的语义知识超图存储研究宋雪雁，张伟民，张祥青（吉林大学商学与管理学院，长春130012）摘要针对资源描述框架（resourcedescriptionframework，RDF）存储效率低、难以存储复杂语义关系等问题，本研究引入超图理论，探索一种融合超图理论的语义知识图谱存储模型，以期实现RDF对超图数据的存储，为其他学者利用RDF构建知识超图提供参考。本研究构建了适用于超图结构的语义知识超图（semanticknowledgehypergraph，SKH）模型，与语义知识图谱（semanticknowledgegraph，SKG）进行对比，分析其存储效率与复杂语义关系存储能力，并论述其在知识检索、知识推理、数据转换与可视化等方面的应用。研究结果发现，SKH模型具有比SKG更优的存储效率与复杂语义关系存储能力，SKG的知识检索和知识推理方式也适用于SKH模型，SKH模型数据在一定程度上能与SKG数据相互转换，SKH模型具有更加多元且表意丰富的可视化方式，对于信息资源管理领域复杂语义存储具有重要意义。关键词RDF；语义知识超图；知识存储；超图理论StorageofSemanticKnowledgeHypergraphBasedonaResourceDescriptionFrameworkSongXueyan,ZhangWeiminandZhangXiangqing(SchoolofBusinessandManagement,JilinUniversity,Changchun130012)Abstract：Toaddressthelowstorageefficiencyanddifficultyinstoringcomplexsemanticrelationshipsinaresourcede‐scriptionframework(RDF),thehypergraphtheoryisintroducedtoexploreasemanticknowledgegraphstoragemodelthatintegratesthehypergraphtheorytorealizethestorageofhypergraphdatabasedontheRDFandprovideareferenceforotherscholarstousetheRDFtobuildknowledgehypergraphs.Weconstructasemanticknowledgehypergraph(SKH)modelsuitableforhypergraphs,analyzeitsstorageefficiencyandstoragecapacityofcomplexsemanticrelationsbycom‐paringitwithasemanticknowledgegraph(SKG),anddiscussitsapplicationsinknowledgeretrieval,knowledgereason‐ing,dataconversion,andvisualization.WeestablishedthattheSKHmodelhasbetterstorageefficiencyandcomplexse‐manticrelationshipstoragecapacitythantheSKG.ThemethodsofknowledgeretrievalandknowledgereasoningofSKGarealsoapplicabletoSKH.TheSKHmodeldatacanbetransfor...
