Design of Link Evaluation Method to Improve Reliability based on Linked Open Big Data and Natural Language Processing

  • Authors

    • Yonglak SHON
    • Jaeyoung PARK
    • Jangmook KANG
    • Sangwon LEE
    2018-08-29
    https://doi.org/10.14419/ijet.v7i3.33.18601
  • AI, Big Data, Linked Open Data, NLP, Ontology, Ontology Web Language, Resource Description Framework

  • Abstract

    The LOD data sets consist of RDF Triples based on the Ontology, a specification of existing facts, and by linking them to previously disclosed knowledge based on linked data principles. These structured LOD clouds form a large global data network, which provides a more accurate foundation for users to deliver the desired information. However, it is difficult to identify that, if the presence of the same object is identified differently across several LOD data sets, they are inherently identical. This is because objects with different URIs in the LOD datasets must be different and they must be closely examined for similarities in order to judge them as identical. The aim of this study is that the prosed model, RILE, evaluates similarity by comparing object values of existing specified predicates. After performing experiments with our model, we could check the improvement of the confidence level of the connection by extracting the link value.

     

     

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  • How to Cite

    SHON, Y., PARK, J., KANG, J., & LEE, S. (2018). Design of Link Evaluation Method to Improve Reliability based on Linked Open Big Data and Natural Language Processing. International Journal of Engineering & Technology, 7(3.33), 168-173. https://doi.org/10.14419/ijet.v7i3.33.18601

    Received date: 2018-08-29

    Accepted date: 2018-08-29

    Published date: 2018-08-29