Supervised and unsupervised approaches to the ontology-based Disambiguation of JSON documents

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Abstract

This paper proposes and evaluates certain supervised and unsupervised approaches to Named Entity Disambiguation in JSON documents, for linking of all ambiguous JSON objects to their most appropriate candidate DBpedia ontology classes. We achieve this by taking into account knowledge about the hierarchal structure of the document and two kinds of scores, namely Sibling Relatedness and Parental Relatedness, along with textual similarity between a class and the object indicated by the Textual Similarity score.

Original languageEnglish
Pages (from-to)295-307
Number of pages13
JournalCEUR Workshop Proceedings
Volume2086
Publication statusPublished - 2017
Event25th Irish Conference on Artificial Intelligence and Cognitive Science, AICS 2017 - Dublin, Ireland
Duration: 7 Dec 20178 Dec 2017

Keywords

  • JSON disambiguation
  • Linked Data
  • Named Entity Disambiguation
  • Ontology Mapping

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