Now showing items 1-13 of 13

  • 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 reasoning for matching SMARTHOUSE technology to people's needs 

    Wiratunga, Nirmalie; Craw, Susan; Taylor, Bruce J. (Elsevier http://www.elsevier.com/wps/find/journaldescription.cws_home/525448/description#description, 2004)
    WIRATUNGA, N., CRAW, S. and TAYLOR, B., 2004. Case-based reasoning for matching SMARTHOUSE technology to people's needs. Knowledge based systems, 17 (2-4), pp. 139-146
    SMARTHOUSE technology offers devices that help the elderly and people with disabilities to live independently in their homes. This paper presents our experiences from a pilot project applying case-based reasoning techniques ...
  • Consultant-2: Pre- and post-processing of machine learning applications. 

    Sleeman, D.; Rissakis, M.; Craw, Susan; Graner, N.; Sharma, S. (Elsevier http://dx.doi.org/10.1006/ijhc.1995.1035, 1995-07)
    SLEEMAN, D., RISSAKIS, M., CRAW, S., GRANER, N. and SHARMA, S., 1995. Consultant-2: Pre- and post processing of machine learning applications. International Journal of Human Computer Studies, 43 (1), pp. 43-63
    The knowledge acquisition bottleneck in the development of large knowledge-based applications has not yet been resolved. One approach which has been advocated is the systematic use of Machine Learning (ML) techniques. ...
  • Design, innovation and case-based reasoning 

    Goel, Ashok K.; Craw, Susan (Cambridge University Press http://dx.doi.org/10.1017/S0269888906000609, 2005)
    GOEL, A. and CRAW, S., 2005. Design, innovation and case-based reasoning. Knowledge Engineering Review, 20 (3), pp. 271-276
    The design task is especially appropriate for applying, integrating, exploring and pushing the boundaries of case-based reasoning. In this paper, we briefly review the challenges that design poses for case-based reasoning ...
  • Fall prediction using behavioural modelling from sensor data in smart homes. 

    Forbes, Glenn; Massie, Stewart; Craw, Susan
    FORBES, G., MASSIE, S. and CRAW, S. [2019]. Fall prediction using behavioural modelling from sensor data in smart homes. Artificial intelligence review [online], (accepted). Available from: https://doi.org/10.1007/s10462-019-09687-7
    The number of methods for identifying potential fall risk is growing as the rate of elderly fallers continues to rise in the UK. Assessments for identifying risk of falling are usually performed in hospitals and other ...
  • Improving e-learning recommendation by using background knowledge. 

    Mbipom, Blessing; Craw, Susan; Massie, Stewart (Wiley https://doi.org/10.1111/exsy.12265, 2018-01-26)
    MBIPOM, B., CRAW, S. and MASSIE, S. 2018. Improving e-learning recommendation by using background knowledge. Expert systems [online], Early View. Available from: https://doi.org/10.1111/exsy.12265
    There is currently a large amount of e-Learning resources available to learners on the Web. However, learners often have difficulty finding and retrieving relevant materials to support their learning goals because they ...
  • Knowledge modelling for a generic refinement framework 

    Boswell, Robin; Craw, Susan (Elsevier http://dx.doi.org/10.1016/S0950-7051(99)00018-0, 1999-10)
    BOSWELL, R. and CRAW, S., 1999. Knowledge modelling for a generic refinement framework. Knowledge Based Systems, 12 (5-6), pp. 317-325
    Refinement tools assist with debugging the knowledge-based system (KBS), thus easing the well-known knowledge acquisition bottleneck, and the more recently recognised maintenance overhead. The existing refinement tools ...
  • 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, ...
  • Learning pseudo-tags to augment sparse tagging in hybrid music recommender systems. 

    Horsburgh, Ben; Craw, Susan; Massie, Stewart (Elsevier http://dx.doi.org/10.1016/j.artint.2014.11.004, 2015-02)
    HORSBURGH, B., CRAW, S. and MASSIE, S., 2015. Learning pseudo-tags to augment sparse tagging in hybrid music recommender systems. Artificial Intelligence, 219, pp. 25-39.
    Online recommender systems are an important tool that people use to find new music. To generate recommendations, many systems rely on tag representations of music. Such systems however suffer from tag sparsity, whereby tracks ...
  • 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 ...
  • Refinement complements verification and validation 

    Craw, Susan (Elsevier http://dx.doi.org/10.1006/ijhc.1996.0012, 1996-02)
    CRAW, S., 1996. Refinement complements verification and validation. International Journal of Human Computer Studies, 44 (2), pp. 245-256
    Knowledge based systems are being applied in ever increasing numbers. The development of knowledge acquisition tools has eased the “Knowledge Acquisition Bottleneck”. More recently there has been a demand for mechanisms ...
  • Refinement in response to validation. 

    Craw, Susan; Sleeman, D. (Elsevier http://dx.doi.org/10.1016/0957-4174(94)E0025-P, 1995-07)
    CRAW, S. and SLEEMAN, D., 1995. Refinement in response to validation. Expert Systems with Applications, 8 (3), pp. 343-349
    Knowledge-based systems (KBSs) are being applied in ever increasing numbers. In parallel with the development of knowledge acquisition tools is the demand for mechanisms to assure their quality, particularly in safety ...
  • Retrieval, reuse, revision and retention in case-based reasoning 

    Craw, Susan (Cambridge University Press http://dx.doi.org/10.1017/S0269888906000646, 2005)
    De Mantaras, Ramon Lopez et al, 2005. Retrieval, reuse, revision and retention in case-based reasoning. Knowledge Engineering Review, 20 (3), pp. 215-240.
    Case-based reasoning (CBR) is an approach to problem solving that emphasizes the role of prior experience during future problem solving (i.e., new problems are solved by reusing and if necessary adapting the solutions to ...