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Computationally efficient ontology selection in software requirement planning

Author

Listed:
  • R. B. K. Brown

    (University of Wollongong)

  • G. Beydoun

    (University of Wollongong)

  • G. Low

    (University of New South Wales)

  • W. Tibben

    (University of Wollongong)

  • R. Zamani

    (University of Wollongong)

  • F. García-Sánchez

    (University of Valencia)

  • R. Martinez-Bejar

    (University of Valencia)

Abstract

Understanding the needs of stakeholders and prioritizing requirements are the vital steps in the development of any software application. Enabling tools to support these steps have a critical role in the success of the corresponding software application. Based on such a critical role, this paper presents a computationally efficient ontology selection in software requirement planning. The key point guiding the underlying design is that, once gathered, requirements need to be processed by decomposition towards the generation of a specified systems design. A representational framework allows for the expression of high level abstract conceptions under a single schema, which may then be made explicit in terms of axiomatic relations and expressed in a suitable ontology. The initial experimental results indicate that our framework for filtered selection of a suitable ontology operates in a computationally efficient manner.

Suggested Citation

  • R. B. K. Brown & G. Beydoun & G. Low & W. Tibben & R. Zamani & F. García-Sánchez & R. Martinez-Bejar, 2016. "Computationally efficient ontology selection in software requirement planning," Information Systems Frontiers, Springer, vol. 18(2), pages 349-358, April.
    • Handle: RePEc:spr:infosf:v:18:y:2016:i:2:d:10.1007_s10796-014-9540-3
    DOI: 10.1007/s10796-014-9540-3
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    References listed on IDEAS

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    1. I-Ching Hsu, 2013. "Personalized web feeds based on ontology technologies," Information Systems Frontiers, Springer, vol. 15(3), pages 465-479, July.
    2. Álvaro Carrera & Carlos A. Iglesias & Mercedes Garijo, 2014. "Beast methodology: An agile testing methodology for multi-agent systems based on behaviour driven development," Information Systems Frontiers, Springer, vol. 16(2), pages 169-182, April.
    3. Nicola Guarino & Daniel Oberle & Steffen Staab, 2009. "What Is an Ontology?," International Handbooks on Information Systems, in: Steffen Staab & Rudi Studer (ed.), Handbook on Ontologies, pages 1-17, Springer.
    4. Csaba Veres & Jennifer Sampson & Karl Cox & Steven Bleistein & June Verner, 2010. "An Ontology-Based Approach for Supporting Business-IT Alignment," Springer Optimization and Its Applications, in: Fatos Xhafa & Leonard Barolli & Petraq J. Papajorgji (ed.), Complex Intelligent Systems and Their Applications, chapter 0, pages 21-42, Springer.
    5. Steffen Staab & Rudi Studer (ed.), 2009. "Handbook on Ontologies," International Handbooks on Information Systems, Springer, number 978-3-540-92673-3, December.
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    Cited by:

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    2. Dedi Iskandar Inan & Ghassan Beydoun & Simon Opper, 2018. "Agent-Based Knowledge Analysis Framework in Disaster Management," Information Systems Frontiers, Springer, vol. 20(4), pages 783-802, August.
    3. Kimberly García & Sonia Mendoza & Dominique Decouchant & Patrick Brézillon, 0. "Facilitating resource sharing and selection in ubiquitous multi-user environments," Information Systems Frontiers, Springer, vol. 0, pages 1-21.

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