• DocumentCode
    124182
  • Title

    Learning of Legal Ontology Supporting the User Queries Satisfaction

  • Author

    Mezghanni, Imen Bouaziz ; Gargouri, Faiez

  • Author_Institution
    MIRACL Lab., ISIM, Sfax, Tunisia
  • Volume
    1
  • fYear
    2014
  • fDate
    11-14 Aug. 2014
  • Firstpage
    414
  • Lastpage
    418
  • Abstract
    In recent years, the development of legal ontologies has increased significantly with the diversity of their applications known as complicated due to the complexity of their domain. In the preliminary part of this paper, we introduce the major steps in the learning process, then we present some works interested in Arabic ontology learning. The rest of the paper serves to propose our approach for ontology learning from Tunisian Legal Texts designed for legal information retrieval. The search process that we suggest exploits the user´s profile and uses a query reformulation mechanism based on the learned ontology. The purpose of the system is to satisfy a user´s specific retrieval requirement by finding the best response to his request.
  • Keywords
    learning (artificial intelligence); natural language processing; ontologies (artificial intelligence); query formulation; query processing; user interfaces; Arabic ontology learning process; Tunisian legal texts; legal information retrieval; legal ontology; query reformulation mechanism; search process; user profile; user queries satisfaction; Context; Information retrieval; Law; Ontologies; Pragmatics; Semantics; legal information retrieval system; legal ontology learning; query reformulation mechanism;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2014 IEEE/WIC/ACM International Joint Conferences on
  • Conference_Location
    Warsaw
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2014.64
  • Filename
    6927573