Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Repairing Hidden Links in Linked Data
Year:2017
Research Areas
  • Information technology and adata processing
Information
Abstract
artificial intelligence applications. Linked Data, as a method of publishing KGs, allows applications to traverse within, and even out of, the graph thanks to global dereferenceable identifiers denoting entities, in the form of IRIs. However, as we show in this work, after analyzing several popular datasets (namely DBpedia, LOD Cache, and Web Data Commons JSON-LD data) many entities are being represented using literal strings where IRIs should be used, diminishing the advantages of using Linked Data. To remedy this, we propose an approach for identifying such strings and replacing them with their corresponding entity IRIs. The proposed approach is based on identifying relations between entities based on both ontological axioms as well as data profiling information and converting strings to entity IRIs based on the types of entities linked by each relation. Our approach showed 98% recall and 76% precision in identifying such strings and 97% precision in converting them to their corresponding IRI in the considered KG. Further, we analyzed how the connectivity of the KG is increased when new relevant links are added to the entities as a result of our method. Our experiments on a subset of the Spanish DBpedia data show that it could add 25% more links to the KG and improve the overall connectivity by 17%
International
Si
Congress
K-CAP 2017
960
Place
Austin, Estados Unidos
Reviewers
Si
ISBN/ISSN
978-1-4503-5553-7
10.1145/3148011.3148020
Start Date
04/12/2017
End Date
06/12/2017
From page
1
To page
8
Proceedings of the Knowledge Capture Conference
Participants
  • Autor: Nandana Sampath Mihindukulasooriya (UPM)
  • Autor: Mariano Rico Almodovar (UPM)
  • Autor: Idafen Santana Perez (UPM)
  • Autor: Raul Garcia Castro (UPM)
  • Autor: Asuncion de Maria Gomez Perez (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Ontology Engineering Group
  • Departamento: Inteligencia Artificial
  • Departamento: Arquitectura y Tecnología de Sistemas Informáticos
S2i 2019 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)