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http://dx.doi.org/10.7472/jksii.2018.19.3.67

Implementation of Policy based In-depth Searching for Identical Entities and Cleansing System in LOD Cloud  

Kim, Kwangmin (AI Lab., Saltlux)
Sohn, Yonglak (Dept. of Computer Engineering, Seokyeong University)
Publication Information
Journal of Internet Computing and Services / v.19, no.3, 2018 , pp. 67-77 More about this Journal
Abstract
This paper suggests that LOD establishes its own link policy and publishes it to LOD cloud to provide identity among entities in different LODs. For specifying the link policy, we proposed vocabulary set founded on RDF model as well. We implemented Policy based In-depth Searching and Cleansing(PISC for short) system that proceeds in-depth searching across LODs by referencing the link policies. PISC has been published on Github. LODs have participated voluntarily to LOD cloud so that degree of the entity identity needs to be evaluated. PISC, therefore, evaluates the identities and cleanses the searched entities to confine them to that exceed user's criterion of entity identity level. As for searching results, PISC provides entity's detailed contents which have been collected from diverse LODs and ontology customized to the content. Simulation of PISC has been performed on DBpedia's 5 LODs. We found that similarity of 0.9 of source and target RDF triples' objects provided appropriate expansion ratio and inclusion ratio of searching result. For sufficient identity of searched entities, 3 or more target LODs are required to be specified in link policy.
Keywords
Linked Open Data; Searching Identical Entity; Link Policy; Ontology; Semantic Web;
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