Now showing items 1-9 of 9

  • Case-base maintenance with multi-objective evolutionary algorithms. 

    Lupiani, Eduardo; Massie, Stewart; Craw, Susan; Juarez, Jose M.; Palma, Jose T. (Springer https://dx.doi.org/10.1007/s10844-015-0378-z, 2015-09-21)
    LUPIANI, E., MASSIE, S., CRAW, S., JUAREZ, J.M. and PALMA, J., 2016. Case-base maintenance with multi-objective evolutionary algorithms. Journal of Intelligent Information Systems, Vol 46(2), pp. 259-284.
    Case-Base Reasoning is a problem-solving methodology that uses old solved problems, called cases, to solve new problems. The case-base is the knowledge source where the cases are stored, and the amount of stored cases is ...
  • Case-based situation awareness. 

    Nwiabu, Nuka D.; Allison, Ian K.; Holt, Patrik; Lowit, Peter; Oyeneyin, Babs (IEEE http://dx.doi.org/10.1109/CogSIMA.2012.6188388, 2012)
    NWIABU, N., ALLISON, I., HOLT, P., LOWIT, P. and OYENEYIN, B., 2012. Case-based situation awareness. In: IEEE Multi-disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support. 6-8 March 2012. Piscataway, New Jersey: IEEE. Pp. 22-29.
    Situation-aware case-based decision support (SACBDS) systems comprise two distinct parts: situation awareness (SA) and case-based reasoning (CBR). The SA part keeps a finite history of the time space information of the ...
  • Complexity modelling for case knowledge maintenance in case-based reasoning. 

    Massie, Stewart (The Robert Gordon University School of Computing, 2006-12)
    Case-based reasoning solves new problems by re-using the solutions of previously solved similar problems and is popular because many of the knowledge engineering demands of conventional knowledge-based systems are removed. ...
  • A knowledge acquisition tool to assist case authoring from texts. 

    Asiimwe, Stella Maris (The Robert Gordon University School of Computing, 2009-03)
    Case-Based Reasoning (CBR) is a technique in Artificial Intelligence where a new problem is solved by making use of the solution to a similar past problem situation. People naturally solve problems in this way, without ...
  • Learning adaptation knowledge to improve case-based reasoning 

    Craw, Susan; Wiratunga, Nirmalie; Rowe, Ray (Elsevier http://dx.doi.org/10.1016/j.artint.2006.09.001, 2006-11)
    CRAW, S., WIRATUNGA, N. and ROWE, R., 2006. Learning adaptation knowledge to improve case-based reasoning. Artificial Intelligence, 170 (16-17), pp. 1175-1192.
    Case-Based Reasoning systems retrieve and reuse solutions for previously solved problems that have been encountered and remembered as cases. In some domains, particularly where the problem solving is a classification task, ...
  • Maintaining retrieval knowledge in a case-based reasoning system. 

    Craw, Susan; Jarmulak, Jacek; Rowe, Ray (Blackwell http://www.blackwellpublishing.com/journal.asp?ref=0824-7935&site=1, 2001-05)
    CRAW, S., JARMULAK, J. and ROWE, R., 2001. Maintaining retrieval knowledge in a case-based reasoning system. Computational Intelligence, 17 (2), pp. 346-363.
    The knowledge stored in a case-base is central to the problem-solving of a Case-Based Reasoning (CBR) system. Therefore, case-base main- tenance is a key component of maintaining a CBR system. However, other knowledge ...
  • Plan recommendation for well engineering. 

    Thomson, Richard; Massie, Stewart; Craw, Susan; Ahriz, Hatem; Mills, Ian (Springer http://dx.doi.org/10.1007/978-3-642-21827-9_45, 2011-07)
    THOMSON, R., MASSIE, S., CRAW, S., AHRIZ, H. and MILLS, I., 2011. Plan recommendation for well engineering. In: K. G. MEHOTRA, C. K. MOHAN, J. C. OH, P. K. VARSHNEY and M. ALI, eds. Modern Approaches in Applied Intelligence: Proceedings of the 24th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, Part II. 28 June – 1 July 2011. Berlin: Springer. Pp. 436-445.
    Good project planning provides the basis for successful offshore well drilling projects. In this domain, planning occurs in two phases: an onshore phase develops a project plan; and an offshore phase implements the plan ...
  • Self-optimising CBR retrieval 

    Jarmulak, Jacek; Craw, Susan; Rowe, Ray (IEEE, 2000-11)
    JARMULAK, J., CRAW, S. and ROWE, R. 2000. Self-optimising CBR retrieval. In: Proceedings of the 12th IEEE International Conference on Tools with Artificial Intelligence. 13-15 November 2000. Vancouver, Canada. pp.376-383.
    One reason why Case-Based Reasoning (CBR) has become popular is because it reduces development cost compared to rule-based expert systems. Still, the knowledge engineering effortmay be demanding. In this paper we ...
  • Situation awareness in context-aware case-based decision support. 

    Nwiabu, Nuka D.; Allison, Ian K.; Holt, Patrik; Lowit, Peter; Oyeneyin, Babs (IEEE http://dx.doi.org/10.1109/COGSIMA.2011.5753761, 2011-02)
    NWIABU, N., ALLISON, I., HOLT, P., LOWIT, P. and OYENEYIN, B., 2011. Situation awareness in context-aware case-based decision support. In: IEEE Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA 2011). 22-24 February 2011. Piscataway, New Jersey: IEEE. Pp. 9-16
    Humans naturally reuse recalled knowledge to solve problems and this includes understanding the information that identify or characterize these problems (context), and the situation. Context-aware case-based reasoning ...