Now showing items 25-36 of 36

  • Monitoring health in smart homes using simple sensors. 

    Massie, Stewart; Forbes, Glenn; Craw, Susan; Fraser, Lucy; Hamilton, Graeme (ICCBR (Organisers) http://ceur-ws.org/Vol-2148/, 2018-07-13)
    MASSIE, S., FORBES, G., CRAW, S., FRASER, L. and HAMILTON, G. 2018. Monitoring health in smart homes using simple sensors. In Bach, K., Bunescu, R., Farri, O., Guo, A., Hasan, S., Ibrahim, Z.M., Marling, C., Raffa, J., Rubin, J. and Wu, H. (eds.) Proceedings of the 3rd International workshop on knowledge discovery in healthcare data co-located with the 27th International joint conference on artificial intelligence and the 23rd European conference on artificial intelligence (IJCAI-ECAI 2018), 13 July 2018, Stockholm, Sweden. Stockholm: CEUR [online], pages 33-37. Available from: http://ceur-ws.org/Vol-2148/paper05.pdf
    We consider use of an ambient sensor network, installed in Smart Homes, to identify low level events taking place which can then be analysed to generate a resident's profile of activities of daily living (ADLs). These ADL ...
  • A multi-objective evolutionary algorithm fitness function for case-base maintenance. 

    Lupiani, Eduardo; Craw, Susan; Massie, Stewart; Juarez, Jose M.; Palma, Jose T. (Springer. http://dx.doi.org/10.1007/978-3-642-39056-2_16, 2013-07)
    LUPIANI, E., CRAW, S., MASSIE, S., JUAREZ, J. M. and PALMA, J. T., 2013. A multi-objective evolutionary algorithm fitness function for case-base maintenance. In: S. J. DELANY and S. ONTANON, eds. Case-Based Reasoning Research and Development: Proceedings of the 21st International Conference, ICCBR 2013. 8-11 July 2013. Berlin: Springer. Pp. 218-232.
    Case-Base Maintenance (CBM) has two important goals. On the one hand, it aims to reduce the size of the case-base. On the other hand, it has to improve the accuracy of the CBR system. CBM can be represented as a ...
  • Music recommendation: audio neighbourhoods to discover music in the long tail. 

    Craw, Susan; Horsburgh, Ben; Massie, Stewart (Springer https://dx.doi.org/10.1007/978-3-319-24586-7_6, 2015-11-26)
    CRAW, S., HORSBURGH, B. and MASSIE, S. 2015. Music recommendation: audio neighbourhoods to discover music in the long tail. Lecture notes in computer science [online], 9343, Proceedings of the 23rd international conference on case-based reasoning (ICCBR 2015), pages 73-87. Available from: https://dx.doi.org/10.1007/978-3-319-24586-7_6
    Millions of people use online music services every day and recommender systems are essential to browse these music collections. Users are looking for high quality recommendations, but also want to discover tracks and artists ...
  • Music recommenders: user evaluation without real users? 

    Craw, Susan; Horsburgh, Ben; Massie, Stewart (AAAI/International Joint Conferences on Artificial Intelligence (IJCAI) http://ijcai.org/papers15/Papers/IJCAI15-249.pdf, 2015-07)
    CRAW, S., HORSBURGH, B. and MASSIE, S., 2015. Music recommenders: user evaluation without real users? In: Q. YANG and M. WOOLDRIDGE, eds. Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. 25-31 July 2015. [online] Palo Alto: AAAI/IJCAI pp. 1749-1755. Available from: http://ijcai.org/papers15/contents.php [Accessed 10 August 2015]
    Good music recommenders should not only suggest quality recommendations, but should also allow users to discover new/niche music. User studies capture explicit feedback on recommendation quality and novelty, but can ...
  • Music-inspired texture representation. 

    Horsburgh, Ben; Craw, Susan; Massie, Stewart (AAAI Press. http://www.aaai.org/Press/Proceedings/aaai12.php, 2012-07)
    HORSBURGH, B., CRAW, S. and MASSIE, S., 2012. Music-inspired texture representation. In: Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12). 22-26 July 2012. Palo Alto, CA: AAAI Press. Pp. 52-58.
    Techniques for music recommendation are increasingly relying on hybrid representations to retrieve new and exciting music. A key component of these representations is musical content, with texture being the most ...
  • Ontology alignment based on word embedding and random forest classification. 

    Nkisi-Orji, Ikechukwu; Wiratunga, Nirmalie; Massie, Stewart; Hui, Kit-Ying; Heaven, Rachel
    NKISI-ORJI, I., WIRATUNGA, N., MASSIE, S., HUI, K.-Y. and HEAVEN, R. [2018]. Ontology alignment based on word embedding and random forest classification. In Lecture notes in computer science [online]: proceedings of the European conference on machine learning and principles and practice of knowledge discovery in databases (ECML PKDD 2018), 10-14 September 2018, Dublin, Ireland. Basel: Springer, (accepted).
    Ontology alignment is crucial for integrating heterogeneous data sources and forms an important component for realising the goals of the semantic web. Accordingly, several ontology alignment techniques have been proposed ...
  • Opinion context extraction for aspect sentiment analysis. 

    Bandhakavi, Anil; Wiratunga, Nirmalie; Massie, Stewart; Luhar, Rushi (AAAI Press https://www.aaai.org/ocs/index.php/ICWSM/ICWSM18/paper/view/17859, 2018-06-15)
    BANDHAKAVI, A., WIRATUNGA, N., MASSIE, S. and LUHAR, R. 2018. Opinion context extraction for aspect sentiment analysis. In Proceedings of 12th International Association for the Advancement of Artificial Intelligence (AAAI) conference on web and social media 2018 (ICWSM 2018), 25-28 June 2018, Palo Alto, USA. Palo Alto: AAAI Press [online], pages 564-567. Available from: https://www.aaai.org/ocs/index.php/ICWSM/ICWSM18/paper/view/17859/17051
    Sentiment analysis is the computational study of opinionated text and is becoming increasing important to online commercial applications. However, the majority of current approaches determine sentiment by attempting to ...
  • Personalised human activity recognition using matching networks. 

    Sani, Sadiq; Wiratunga, Nirmalie; Massie, Stewart; Cooper, Kay (Springer https://doi.org/10.1007/978-3-030-01081-2_23, 2018-10-09)
    SANI, S., WIRATUNGA, N., MASSIE, S. and COOPER, K. 2018. Personalised human activity recognition using matching networks. In Cox, M.T., Funk, P. and Begum, S. (eds.) Lecture notes in computer science, 11156. Case-based reasoning research and development; proceedings of the 26th International conference on case-based reasoning (ICCBR-18), 9-12 July 2018, Stockholm, Sweden. Cham: Springer [online], pages 339-353. Available from: https://doi.org/10.1007/978-3-030-01081-2_23
    Human Activity Recognition (HAR) is typically modelled as a classification task where sensor data associated with activity labels are used to train a classifier to recognise future occurrences of these activities. An ...
  • 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 ...
  • Role of semantic indexing for text classification. 

    Sani, Sadiq (Robert Gordon University School of Computing Science and Digital Media, 2014-09)
    The Vector Space Model (VSM) of text representation suffers a number of limitations for text classification. Firstly, the VSM is based on the Bag-Of-Words (BOW) assumption where terms from the indexing vocabulary are ...
  • SelfBACK: Activity recognition for self-management of low back pain. 

    Sani, Sadiq; Wiratunga, Nirmalie; Massie, Stewart; Cooper, Kay (Springer https://dx.doi.org/10.1007/978-3-319-47175-4, 2016-11-05)
    SANI, S., WIRATUNGA, N., MASSIE, S. and COOPER, K. 2016. SelfBACK: Activity recognition for self-management of low back pain. In Bramer, M. and Petridis, M. (eds.) 2016. Research and development in intelligent systems XXXIII: incorporating applications and innovations in intelligent systems XXIV: proceedings of the 36th SGAI nternational conference on innovative techniques and applications of artificial intelligence (AI-2016), 13-15 December 2016, Cambridge, UK. Cham: Springer [online], pages 281-294. Available from: http://dx.doi.org/10.1007/978-3-319-47175-4
    Low back pain (LBP) is the most significant contributor to years lived with disability in Europe and results in significant financial cost to European economies. Guidelines for the management of LBP have self-management ...
  • Taxonomic corpus-based concept summary generation for document annotation. 

    Nkisi-Orji, Ikechukwu; Wiratunga, Nirmalie; Hui, Kit-Ying; Heaven, Rachel; Massie, Stewart (Springer https://doi.org/10.1007/978-3-319-67008-9_5, 2017-09-02)
    NKISI-ORJI, I., WIRATUNGA, N., HUI, K.-Y., HEAVEN, R. and MASSIE, S. 2017. Taxonomic corpus-based concept summary generation for document annotation. In Kampus, J., Tsakonas, G., Manolopoulos, Y., Iliadis, L. and Karydis, I. (eds). Lecture notes in computer science [online], 10450, research and advanced technology for digital libraries: proceedings of the 21st international conference on theory and practice of digital libraries (TPDL 2017), 18-21 September 2017, Thessaloniki, Greece. Cham: Springer [online], pages 49-60. Available from: https://doi.org/10.1007/978-3-319-67008-9_5
    Semantic annotation is an enabling technology which links documents to concepts that unambiguously describe their content. Annotation improves access to document contents for both humans and software agents. However, the ...