An empirical evaluation of ontology-based semantic annotators

  • Authors:
  • Srecko Joksimovic;Jelena Jovanovic;Dragan Gasevic;Amal Zouaq;Zoran Jeremic

  • Affiliations:
  • Simon Fraser University, Burnaby, Canada;University of Belgrade, Belgrade, Serbia;Athabasca University, Athabasca, Canada;Royal Military College of Canada, Kingston, Canada;Ryerson University, Toronto, Canada

  • Venue:
  • Proceedings of the seventh international conference on Knowledge capture
  • Year:
  • 2013

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Abstract

One of the most important prerequisites for achieving the Semantic Web vision is semantic annotation of data/resources. Semantic annotation enriches unstructured and/or semistructured content with a context that is further linked to the structured domain-specific knowledge. In particular, ontologybased semantic annotators enable the selection of a specific ontology to annotate content. This paper presents results of an empirical study of recent ontology-based annotators, namely Stanbol, KIM, and SDArch. Specifically, we evaluated the robustness of these annotators with respect to specific features of ontology concepts such as the length of concepts? labels and their linguistic categories (e.g., prepositions and conjunctions). Our results show that although significantly correlated according to most of the conducted evaluations, tools still exhibit their unique features that could be a topic of new research.