• DocumentCode
    3740102
  • Title

    Answering N-Relation Natural Language Questions in the Commercial Domain

  • Author

    Elena Cabrio;Catherine Faron Zucker;Fabien Gandon;Amine Hallili;Andrea Tettamanzi

  • Author_Institution
    Inria Sophia Antipolis Mediterranee, Sophia Antipolis, France
  • Volume
    1
  • fYear
    2015
  • Firstpage
    169
  • Lastpage
    172
  • Abstract
    This paper presents SynchroBot, a Natural Language Question Answering system in the Commercial Domain. It relies on an RDF dataset and an RDFS ontology that we have developed for the commercial domain of the mobile phone industry. We propose an approach to understand and interpret natural language questions, based on the use of regular expressions to identify both the properties connecting entities, and their values. These regex are automatically learned from a subset of our dataset with a genetic algorithm.
  • Keywords
    "Ontologies","Cellular phones","Joining processes","Natural languages","Mobile handsets","Genetics","Sociology"
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology (WI-IAT), 2015 IEEE / WIC / ACM International Conference on
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2015.51
  • Filename
    7396798