Metaheuristic for Word Sense Disambiguation: A Review

  • Authors

    • Wafaa AL-Saiagh
    • Sabrina Tiun
    • Ahmed AL-Saffar
    • Suryanti Awang
    • A S. Al-khaleefa
    https://doi.org/10.14419/ijet.v7i3.30.19091
  • Word Sense Disambiguation, Machine learning Techniques, Semantic Similarity Measurement-Heuristic, Natural Language Processing.

  • Abstract

    Word Sense Disambiguation (WSD) is the process of determining the exact sense of a particular word in accordance to the context in a computational manner. Such task plays an essential role in multiple fields of study such as Information Retrieval and Information Extraction. With the complexity of human language, WSD came up to solve the problem behind the ambiguity between senses in which a single word would yield different meaning. In this vein, determining the exact meaning of the certain word would facilitate the process of identifying the category of such text, accurate corresponding search results and providing an accurately summarized portion. Several approaches have been proposed for the WSD including statistical, semantic and machine learning techniques. This paper aims to provide a review of such approaches by tackling and categorizing the related works in accordance to the main types.

     

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  • How to Cite

    AL-Saiagh, W., Tiun, S., AL-Saffar, A., Awang, S., & S. Al-khaleefa, A. (2018). Metaheuristic for Word Sense Disambiguation: A Review. International Journal of Engineering & Technology, 7(3.30), 211-217. https://doi.org/10.14419/ijet.v7i3.30.19091

    Received date: 2018-09-06

    Accepted date: 2018-09-06