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Resource propagation algorithm considering predicates to complement knowledge bases in linked data

机译:考虑谓词链接数据中的补充知识库的资源传播算法

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摘要

Linked data are directed graph data with descriptive labels using uniform resource identifiers (URI) and based on resource description framework (RDF). Linked data which are published as open data on the web are called linked open data (LOD). LOD is popular as a technology for constructing the semantic web because it can create a knowledge base by linking various resources. However, a large amount of the linked data does not have sufficient links since resources defined by URI type are scarce. Therefore, this paper presents a new resource propagation algorithm (RPA) which predicts links between resources in the linked data, and complements the knowledge bases by considering predicates in the RDF structure. The presented experiment demonstrates that the RPA was able to complement semantic links between resources considering each predicate.
机译:链接数据是使用统一资源标识符(URI)的描述性标签的指示图数据,并基于资源描述框架(RDF)。 已发布为Web上的打开数据的链接数据称为链接开放数据(LOD)。 LOD作为构建语义Web的技术很受欢迎,因为它可以通过链接各种资源来创建知识库。 但是,由于URI类型定义的资源是稀缺的,因此大量的链接数据没有足够的链接。 因此,本文提出了一种新的资源传播算法(RPA),其预测链接数据中资源之间的链接,并通过考虑RDF结构的谓词来补充知识库。 所呈现的实验表明,RPA能够在考虑每个谓词之间补充资源之间的语义链接。

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