• DocumentCode
    3723124
  • Title

    Arabic Terminology Extraction and Enrichment Based on Domain-Specific Text Mining

  • Author

    Wiem Lahbib;Ibrahim Bounhas;Yahya Slimani

  • Author_Institution
    Lab. of Comput. Sci. for Ind. Syst., Carthage Univ., Charguia, Tunisia
  • fYear
    2015
  • Firstpage
    340
  • Lastpage
    347
  • Abstract
    Information Retrieval (IR) involves several disciplines to improve the search quality. In this paper, we focus on terminology extraction which includes critical tasks especially for highly ambiguous languages like Arabic. Properly retrieving a list of relevant terms for a given domain and enrich it is a persistent problem. Therefore, and in order to improve the coverage of terminology extraction and enrichment, we must strengthen our research by text-mining technologies based on well-founded methods. In this article, we present a new Arabic terminology extraction and enrichment approach which exploits the corpus structure as a first step to extract a minimal terminology and uses text-mining techniques to enrich it in a second step.
  • Keywords
    "Terminology","Semantics","Text mining","Pragmatics","Feature extraction","Ontologies","Calculus"
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence (ICTAI), 2015 IEEE 27th International Conference on
  • ISSN
    1082-3409
  • Type

    conf

  • DOI
    10.1109/ICTAI.2015.59
  • Filename
    7372155