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Comparison Semantic Similarity Approach Using Biomedical Domain Dataset

Author

Listed:
  • Shahreen Kasim

    (Department Web Technology)

  • Nurul Aswa Omar

    (Department Web Technology)

  • Nurul Suhaida Mohammad Akbar

    (Department Web Technology)

  • Rohayanti Hassan

    (Department Web Technology)

  • Marzanah A. Jabar

    (Soft Computing And Data Mining Centre, Faculty Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor Malaysia)

Abstract

Semantic similarity is defined as the closeness of two concepts, based on the likeliness of their meaning. Most semantic similarity is applied uses ontology. This research are uses ontology as a case study due to their efficiency, scalability, lack of constraints and the availability of large ontologies. Ontology-based semantic similarity is used in two situations. The semantic similarity in a single ontology and when multiple ontologies are involved. In this research focus on single ontology where use MeSH datasets as a case study. Semantic similarity single ontology means similarities are compared from the same ontology. The importance of information in the biomedical field, semantic similarity measures have been of great interest.

Suggested Citation

  • Shahreen Kasim & Nurul Aswa Omar & Nurul Suhaida Mohammad Akbar & Rohayanti Hassan & Marzanah A. Jabar, 2017. "Comparison Semantic Similarity Approach Using Biomedical Domain Dataset," Acta Electronica Malaysia (AEM), Zibeline International Publishing, vol. 1(2), pages 1-4, January.
    • Handle: RePEc:zib:zbnaem:v:1:y:2017:i:2:p:1-4
    DOI: 10.26480/aem.02.2017.01.04
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    References listed on IDEAS

    as
    1. Angelos Hliaoutakis & Giannis Varelas & Epimenidis Voutsakis & Euripides G.M. Petrakis & Evangelos Milios, 2006. "Information Retrieval by Semantic Similarity," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 2(3), pages 55-73, July.
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