• DocumentCode
    2188238
  • Title

    Enhancing Domain Knowledge for Requirements Elicitation with Web Mining

  • Author

    Kaiya, Haruhiko ; Shimizu, Yuutarou ; Yasui, Hirotaka ; Kaijiri, Kenji ; Saeki, Motoshi

  • Author_Institution
    Dept. of Comput. Sci., Shinshu Univ., Nagano, Japan
  • fYear
    2010
  • fDate
    Nov. 30 2010-Dec. 3 2010
  • Firstpage
    3
  • Lastpage
    12
  • Abstract
    To elicit software requirements, we have to have knowledge about a problem domain, e.g., healthcare, shopping or banking where the software is applied. A description of domain knowledge such as a domain ontology helps requirements analysts to elicit requirements completely and correctly to some extent even if they do not have such knowledge sufficiently. Several requirements elicitation methods and tools using domain knowledge description have been thus proposed, but how to develop and to enhance such description is rarely discussed. Summarizing existing documents related to the domain is one of the typical ways to develop such description, and an interview to domain experts is another typical way. However, requirements cannot be elicited completely only with such domain-specific knowledge because a user of such knowledge, i.e., a requirements analyst is not a domain expert in general. Requirements could be also elicited more correctly with both specific and general knowledge because general knowledge sometimes improves understandings of analysts about domain-specific knowledge. In this paper, we propose a method and a tool to enhance an ontology of domain knowledge for requirements elicitation by using Web mining. In our method and our tool, a domain ontology consists of concepts and their relationships. Our method and tool helps an analyst with a domain ontology to mine general concepts necessary for his requirements elicitation from documents on Web and to add such concepts to the ontology. We confirmed enhanced ontologies contribute to improving the completeness and correctness of elicited requirements through a comparative experiment.
  • Keywords
    Internet; data mining; formal specification; formal verification; ontologies (artificial intelligence); systems analysis; Web mining; domain knowledge enhancement; domain ontology; domain specific knowledge; requirement analysis; software requirement elicitation; Books; Conference management; Measurement; Ontologies; Software; Web mining; Web pages; Domain Knowledge; Ontology; Requirements Elicitation; Web Mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering Conference (APSEC), 2010 17th Asia Pacific
  • Conference_Location
    Sydney, NSW
  • ISSN
    1530-1362
  • Print_ISBN
    978-1-4244-8831-5
  • Electronic_ISBN
    1530-1362
  • Type

    conf

  • DOI
    10.1109/APSEC.2010.11
  • Filename
    5693175