A Linked Data Based Approach to Similarity Reasoning

نویسندگان

  • Anna Formica
  • Michele Missikoff
  • Elaheh Pourabbas
  • Francesco Taglino
چکیده

SemSim is a semantic similarity reasoning method that has been conceived to be used as a service for the Semantic Web. SemSim is based on a Weighted Reference Ontology, which is used to semantically annotate a collection of digital resources (e.g., documents) to be searched. In this paper we present a new approach to SemSim implementation based on Linked Data, that significantly increments its usability in the Semantic Web.

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تاریخ انتشار 2013