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

Abstract

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.