Image-Based Literal Node Matching for Linked Data Integration
Takahiro Kawamura, Akihiko Ohsuga · International journal of Web & Semantic Technology · 2014
This paper proposes a method of identifying and aggregating literal nodes that have the same meaning in Linked Open Data (LOD) in order to facilitate cross-domain search.LOD has a graph structure in which most nodes are represented by Uniform Resource Identifiers (URIs), and thus LOD sets are connected and searched through different domains.However, 5% of the values are literal values (strings without URI) even in a de facto hub of LOD, DBpedia.In SPARQL Protocol and RDF Query Language (SPARQL) queries, we need to rely on regular expression to match and trace the literal nodes.Therefore, we propose a novel method, in which part of the LOD graph structure is regarded as a block image, and then the matching is calculated by image features of LOD.In experiments, we created about 30,000 literal pairs from a Japanese music category of DBpedia Japanese and Freebase, and confirmed that the proposed method determines literal identity with F-measure of 76.1-85.0%.