Now showing items 1-7 of 7

  • 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 ...
  • Contextual sentiment analysis for social media genres. 

    Muhammad, Aminu; Wiratunga, Nirmalie; Lothian, Robert (Elsevier http://dx.doi.org/10.1016/j.knosys.2016.05.032, 2016-05-16)
    MUHAMMAD, A., WIRATUNGA, N. and LOTHIAN, R. 2016. Contextual sentiment analysis for social media genres. Knowldege-based systems [online], 108, pages 92-101. Available from: https://dx.doi.org/10.1016/j.knosys.2016.05.032
    The lexicon-based approaches to opinion mining involve the extraction of term polarities from sentiment lexicons and the aggregation of such scores to predict the overall sentiment of a piece of text. It is typically ...
  • Emotion-aware polarity lexicons for Twitter sentiment analysis. 

    Bandhakavi, Anil; Wiratunga, Nirmalie; Massie, Stewart; Padmanabhan, Deepak (Wiley https://doi.org/10.1111/exsy.12332, 2018-10-11)
    BANDHAKAVI, A., WIRATUNGA, N., MASSIE, S. and DEEPAK, P. 2018. Emotion-aware polarity lexicons for Twitter sentiment analysis. Expert systems [online], Early View. Available from: https://doi.org/10.1111/exsy.12332
    Theoretical frameworks in psychology map the relationships between emotions and sentiments. In this paper we study the role of such mapping for computational emotion detection from text (e.g. social media) with a aim to ...
  • Integrating selection-based aspect sentiment and preference knowledge for social recommender systems. 

    Chen, Yoke Yie; Wiratunga, Nirmalie; Lothian, Robert
    CHEN, Y.Y., WIRATUNGA, N. and LOTHIAN, R. [2018]. Integrating selection-based aspect sentiment and preference knowledge for social recommender systems. Online information review [online], (accepted). Available from: https://doi.org/10.1108/OIR-02-2017-0066
    Purpose - Recommender system approaches such as collaborative and content-based filtering rely on user ratings and product descriptions to recommend products. More recently, recommender system research has focused on ...
  • 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, ...
  • Lexicon based feature extraction for emotion text classification. 

    Bandhakavi, Anil; Wiratunga, Nirmalie; Padmanabhan, Deepak; Massie, Stewart (Elsevier https://doi.org/10.1016/j.patrec.2016.12.009, 2016-12-15)
    BANDHAKAVI, A., WIRATUNGA, N., DEEPAK, P. and MASSIE, S. 2017. Lexicon based feature extraction for emotion text classification. Pattern recognition letters [online], 93, pages 133-143. Available from: https://doi.org/10.1016/j.patrec.2016.12.009
    General Purpose Emotion Lexicons (GPELs) that associate words with emotion categories remain a valuable resource for emotion analysis of text. However the static and formal nature of their vocabularies make them inadequate ...
  • Lexicon generation for emotion detection from text. 

    Bandhakavi, Anil; Wiratunga, Nirmalie; Massie, Stewart; Padmanabhan, Deepak (IEEE https://doi.org/10.1109/MIS.2017.22, 2017-02-13)
    BANDHAKAVI, A., WIRATUNGA, N., MASSIE, S. and PADMANABHAN, D. 2017. Lexicon generation for emotion detection from text. IEEE intelligent systems [online], 32(1), pages 102-108. Available from: https://doi.org/10.1109/MIS.2017.22.
    General-purpose emotion lexicons (GPELs) that associate words with emotion categories remain a valuable resource for emotion detection. However, the static and formal nature of their vocabularies make them an inadequate ...