Recent Submissions

  • Predicting service levels using neural networks. 

    Ainslie, Russell; McCall, John; Shakya, Siddhartha; Owusu, Gilbert (Springer https://doi.org/10.1007/978-3-319-71078-5_35, 2017-11-21)
    AINSLIE, R., MCCALL, J., SHAKYA, S. and OWUSU, G. 2017. Predicting service levels using neural networks. In Bramer, M. and Petridis, M. (eds.) Artificial intelligence XXXIV: proceedings of the 37th SGAI International innovative techniques and applications of artificial intelligence conference 2017 (AI 2017), 12-14 December 2017, Cambridge, UK. Lecture notes in computer science, 10630. Cham: Springer [online], pages 411-416. Available from: https://doi.org/10.1007/978-3-319-71078-5_35
    In this paper we present a method to predict service levels in utility companies, giving them advanced visibility of expected service outcomes and helping them to ensure adherence to service level agreements made to their ...
  • Developing accessible services: understanding current knowledge and areas for future support. 

    Crabb, Michael; Heron, Michael James; Jones, Rhianne; Armstrong, Mike; Reid, Hayley; Wilson, Amy
    CRABB, M., HERON, M., JONES, R., ARMSTRONG, M., REID, H. and WILSON, A. 2019. Developing accessible services: understanding current knowledge and areas for future support. In Proceedings of the Conference on human factors in computing systems 2019 (CHI 2019): weaving the threads of CHI, 4-9 May 2019, Glasgow, UK. New York: ACM [online] (accepted). Available from: https://doi.org/10.1145/3290605.3300446
    When creating digital artefacts, it is important to ensure that the product being made is accessible to as much of the population as is possible. Many guidelines and supporting tools exist to assist reaching this goal. ...
  • Context extraction for aspect-based sentiment analytics: combining syntactic, lexical and sentiment knowledge. 

    Bandhakavi, Anil; Wiratunga, Nirmalie; Massie, Stewart; Luhar, Rushi (Springer https://doi.org/10.1007/978-3-030-04191-5_30, 2018-11-16)
    BANDHAKAVI, A., WIRATUNGA, N., MASSIE, S. and LUHAR, R. 2018. Context extraction for aspect-based sentiment analytics: combining syntactic, lexical and sentiment knowledge. In Bramer, M. and PETRIDIS, M. (eds.) Artificial intelligence xxxv: proceedings of the 38th British Computer Society's specialist group on artificial intelligence (SGAI) annual international artificial intelligence conference (AI-2018), 11-13 December 2018, Cambridge, UK. Lecture notes in artificial intelligence, 11311. Cham: Springer [online], pages 357-371. Available from: https://doi.org/10.1007/978-3-030-04191-5_30
    Aspect-level sentiment analysis of customer feedback data when done accurately can be leveraged to understand strong and weak performance points of businesses and services and also formulate critical action steps to improve ...
  • Overlap-based undersampling for improving imbalanced data classification. 

    Vuttipittayamongkol, Pattaramon; Elyan, Eyad; Petrovski, Andrei; Jayne, Chrisina (Springer https://doi.org/10.1007/978-3-030-03493-1_72, 2018-11-09)
    VUTTIPITTAYAMONGKOL, P., ELYAN, E., PETROVSKI, A. and JAYNE, C. 2018. Overlap-based undersampling for improving imbalanced data classification. In Yin, H., Camacho, D., Novais, P. and Tallón-Ballesteros, A. (eds.) Intelligent data engineering and automated learning: proceedings of the 19th International intelligent data engineering and automated learning conference (IDEAL 2018), 21-23 November 2018, Madrid, Spain. Lecture notes in computer science, 11341. Cham: Springer [online], pages 689-697. Available from: https://doi.org/10.1007/978-3-030-03493-1_72
    Classification of imbalanced data remains an important field in machine learning. Several methods have been proposed to address the class imbalance problem including data resampling, adaptive learning and cost adjusting ...
  • Improving human activity recognition with neural translator models. 

    Wijekoon, Anjana; Wiratunga, Nirmalie; Sani, Sadiq (ICCBR (ORGANISERS) http://iccbr18.com/wp-content/uploads/ICCBR-2018-V3.pdf#page=96, 2018-07-09)
    WIJEKOON, A., WIRATUNGA, N. and SANI, S. 2018. Improving human activity recognition with neural translator models. In Minor, M. (ed.) Workshop proceedings for the 26th International conference on case-based reasoning (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Stockholm: ICCBR [online], pages 96-100. Available from: http://iccbr18.com/wp-content/uploads/ICCBR-2018-V3.pdf#page=96
    Multiple sensor modalities provide more accurate Human Activity Recognition (HAR) compared to using a single modality, yet the latter is more convenient and less intrusive. It is advantages to create a model which learns ...
  • Study of similarity metrics for matching network-based personalised human activity recognition. 

    Sani, Sadiq; Wiratunga, Nirmalie; Massie, Stewart; Cooper, Kay (ICCBR (ORGANISERS) http://iccbr18.com/wp-content/uploads/ICCBR-2018-V3.pdf#page=91, 2018-07-09)
    SANI, S., WIRATUNGA, N., MASSIE, S. and COOPER, K. 2018. Study of similarity metrics for matching network-based personalised human activity recognition. In Minor, M. (ed.) Workshop proceedings of the 26th International conference on case-based reasoning (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Stockholm: ICCBR [online], pages 91-95. Available from: http://iccbr18.com/wp-content/uploads/ICCBR-2018-V3.pdf#page=91
    Personalised Human Activity Recognition (HAR) models trained using data from the target user (subject-dependent) have been shown to be superior to non personalised models that are trained on data from a general population ...
  • Explainability through transparency and user control: a case-based recommender for engineering workers. 

    Martin, Kyle; Liret, Anne; Wiratunga, Nirmalie; Owusu, Gilbert; Kern, Mathias (ICCBR (ORGANISERS) http://iccbr18.com/wp-content/uploads/ICCBR-2018-V3.pdf#page=22, 2018-07-09)
    MARTIN, K., LIRET, A., WIRATUNGA, N., OWUSU, G. and KERN, M. 2018. Explainability through transparency and user control: a case-based recommender for engineering workers. In Minor, M. (ed.) Workshop proceedings of the 26th International conference on case-based reasoning (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Stockholm: ICCBR [online], pages 22-31. Available from: http://iccbr18.com/wp-content/uploads/ICCBR-2018-V3.pdf#page=22
    Within the service providing industries, field engineers can struggle to access tasks which are suited to their individual skills and experience. There is potential for a recommender system to improve access to information ...
  • Reasoning with multi-modal sensor streams for m-health applications. 

    Wijekoon, Anjana (ICCBR (ORGANISERS) http://iccbr18.com/wp-content/uploads/ICCBR-2018-V3.pdf#page=234, 2018-07-09)
    WIJEKOON, A. 2018. Reasoning with multi-modal sensor streams for m-health applications. In Minor, M. (ed.) Workshop proceedings of the 26th International conference on case-based reasoning (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Stockholm: ICCBR [online], pages 234-238. Available from: http://iccbr18.com/wp-content/uploads/ICCBR-2018-V3.pdf#page=234
    Musculoskeletal Disorders have a long term impact on individuals as well as on the community. They require self-management, typically in the form of maintaining an active lifestyle that adheres to prescribed exercises ...
  • GramError: a quality metric for machine generated songs. 

    Davies, Craig; Wiratunga, Nirmalie; Martin, Kyle (Springer https://doi.org/10.1007/978-3-030-04191-5_16, 2018-11-16)
    DAVIES, C., WIRATUNGA, N. and MARTIN, K. 2018. GramError: a quality metric for machine generated songs. In Bramer, M. and PETRIDIS, M. (eds.) Artificial intelligence xxxv: proceedings of the 38th British Computer Society's specialist group on artificial intelligence (SGAI) annual international artificial intelligence conference (AI-2018), 11-13 December 2018, Cambridge, UK. Lecture notes in artificial intelligence, 11311. Cham: Springer [online], pages 184-190. Available from: https://doi.org/10.1007/978-3-030-04191-5_16
    This paper explores whether a simple grammar-based metric can accurately predict human opinion of machine-generated song lyrics quality. The proposed metric considers the percentage of words written in natural English and ...
  • Informed pair selection for self-paced metric learning in Siamese neural networks. 

    Martin, Kyle; Wiratunga, Nirmalie; Massie, Stewart; Clos, Jérémie (Springer https://doi.org/10.1007/978-3-030-04191-5_3, 2018-11-16)
    MARTIN, K., WIRATUNGA, N., MASSIE, S. and CLOS, J. 2018. Informed pair selection for self-paced metric learning in Siamese neural networks. In Bramer, M. and PETRIDIS, M. (eds.) Artificial intelligence xxxv: proceedings of the 38th British Computer Society's specialist group on artificial intelligence (SGAI) annual international artificial intelligence conference (AI-2018), 11-13 December 2018, Cambridge, UK. Lecture notes in artificial intelligence, 11311. Cham: Springer [online], pages 34-49. Available from: https://doi.org/10.1007/978-3-030-04191-5_3
    Siamese Neural Networks (SNNs) are deep metric learners that use paired instance comparisons to learn similarity. The neural feature maps learnt in this way provide useful representations for classification tasks. Learning ...
  • Risk information recommendation for engineering workers. 

    Martin, Kyle; Liret, Anne; Wiratunga, Nirmalie; Owusu, Gilbert; Kern, Mathias (Springer https://doi.org/10.1007/978-3-030-04191-5_27, 2018-11-16)
    MARTIN, K., LIRET, A., WIRATUNGA, N., OWUSU, G. and KERN, M. 2018. Risk information recommendation for engineering workers. In Bramer, M. and PETRIDIS, M. (eds.) Artificial intelligence xxxv: proceedings of the 38th British Computer Society's specialist group on artificial intelligence (SGAI) annual international artificial intelligence conference (AI-2018), 11-13 December 2018, Cambridge, UK. Lecture notes in artificial intelligence, 11311. Cham: Springer [online], pages 311-325. Available from: https://doi.org/10.1007/978-3-030-04191-5_27
    Within any sufficiently expertise-reliant and work-driven domain there is a requirement to understand the similarities between specific work tasks. Though mechanisms to develop similarity models for these areas do exist, ...
  • An analysis of indirect optimisation strategies for scheduling. 

    Neau, Charles; Regnier-Coudert, Olivier; McCall, John (IEEE https://doi.org/10.1109/CEC.2018.8477967, 2018-10-04)
    NEAU, C., REGNIER-COUDERT, O. and MCCALL, J. 2018. An analysis of indirect optimisation strategies for scheduling. In Proceedings of Institute of Electrical and Electronics Engineers (IEEE) congress on evolutionary computation (IEEE CEC 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway: IEEE [online], article ID 8477967. Available from: https://doi.org/10.1109/CEC.2018.8477967
    By incorporating domain knowledge, simple greedy procedures can be defined to generate reasonably good solutions to many optimisation problems. However, such solutions are unlikely to be optimal and their quality often ...
  • Tactical plan optimisation for large multi-skilled workforces using a bi-level model. 

    Ainslie, Russell; McCall, John; Shakya, Siddhartha; Owusu, Gilbert (IEEE https://doi.org/10.1109/CEC.2018.8477701, 2018-10-04)
    AINSLIE, R., MCCALL, J., SHAKYA, S. and OWUSU, G. 2018. Tactical plan optimisation for large multi-skilled workforces using a bi-level model. In Proceedings of Institute of Electrical and Electronics Engineers (IEEE) congress on evolutionary computation (IEEE CEC 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway: IEEE [online], article ID 8477701. Available from: https://doi.org/10.1109/CEC.2018.8477701
    The service chain planning process is a critical component in the operations of companies in the service industry, such as logistics, telecoms or utilities. This process involves looking ahead over various timescales to ...
  • Modelling the generalised median correspondence through an edit distance. 

    Moreno-García, Carlos Francisco; Serratosa, Francesc (Springer https://doi.org/10.1007/978-3-319-97785-0_26, 2018-08-02)
    MORENO-GARCÍA, C.F. and SERRATOSA, F. 2018. Modelling the generalised median correspondence through an edit distance. In Bai, X., Hancock, E., Ho, T., Wilson, R., Biggio, B. and Robles-Kelly, A. (eds.) Lecture notes in computer science, 11004: structural, syntactic and statistical pattern recognition: proceedings of the Joint International Association of Pattern Recognition (IAPR) international workshop on structural and syntactic pattern recognition and statistical techniques in pattern recognition (S+SSPR 2018), 17-19 August 2018, Beijing, China. Cham: Springer [online], pages 271-281. Available from: https://doi.org/10.1007/978-3-319-97785-0_26
    On the one hand, classification applications modelled by structural pattern recognition, in which elements are represented as strings, trees or graphs, have been used for the last thirty years. In these models, structural ...
  • Iterated racing algorithm for simulation-optimisation of maintenance planning. 

    Lacroix, Benjamin; McCall, John; Lonchampt, Jérôme (IEEE https://doi.org/10.1109/CEC.2018.8477843, 2018-07-08)
    LACROIX, B., MCCALL, J. and LONCHAMPT, J. 2018. Iterated racing algorithm for simulation-optimisation of maintenance planning. In Proceedings of the Institute of Electrical and Electronics Engineers (IEEE) congress on evolutionary computation 2018 (CEC 2018), 8-13 July 2018, Rio de Janeiro, Brazil. New York: IEEE [online], pages 1-7. Available from: https://doi.org/10.1109/CEC.2018.8477843
    The purpose of this paper is two fold. First, we present a set of benchmark problems for maintenance optimisation called VMELight. This model allows the user to define the number of components in the system to maintain and ...
  • 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 ...
  • CFD modelling of pipe erosion due to sand transport. 

    Ogunsesan, Oluwademilade Adekunle; Hossain, Mamdud; Iyi, Draco; Droubi, Mohamad Ghazi (Springer https://doi.org/10.1007/978-981-13-2273-0_22, 2018-08-28)
    OGUNSESAN, O.A., HOSSAIN, M., IYI, D. and DHROUBI, M.G. 2018. CFD modelling of pipe erosion due to sand transport. In Wahab, M.A. (ed.) Numerical modelling in civil engineering, 2: proceedings of the 1st International conference on numerical modelling in engineering (NME 1018); 28-29 August 2018, Ghent, Belgium. Singapore: Springer [online], pages 274-289. Available from: https://doi.org/10.1007/978-981-13-2273-0_22
    Erosion caused by sand particles is a serious problem facing the oil and gas industry. Predicting pipe erosion due to sand transport is a complex process in multiphase flows due to the complex nature of the flow. Existing ...
  • Lexicon induction for interpretable text classification. 

    Clos, Jérémie; Wiratunga, Nirmalie (Springer https://doi.org/10.1007/978-3-319-67008-9_39, 2017-09-02)
    CLOS, J. and WIRATUNGA, N. 2017. Lexicon induction for interpretable text classification. In Kampus, J., Tsakonas, G., Manolopoulos, Y., Iliadis, L. and Karydis, I. (eds). Lecture notes in computer science, 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 498-510. Available from: https://doi.org/10.1007/978-3-319-67008-9_39
    The automated classification of text documents is an active research challenge in document-oriented information systems, helping users browse massive amounts of data, detecting likely authors of unsigned work, or analyzing ...
  • Deep imitation learning with memory for robocup soccer simulation. 

    Hussein, Ahmed; Elyan, Eyad; Jayne, Chrisina (Springer https://doi.org/10.1007/978-3-319-98204-5_3, 2018-07-27)
    HUSSEIN, A., ELYAN, E. and JAYNE, C. 2018. Deep imitation learning with memory for robocup soccer simulation. In Pimenidis, E. and Jayne, C. (eds.) Communications in computers and information science, 893: engineering applications of neural networks; proceedings of the 19th international engineering applications of neural networks (EANN 2018), 3-5 September 2018, Bristol, UK. Cham: Springer [online], pages 31-43. Available from: https://doi.org/10.1007/978-3-319-98204-5_3
    Imitation learning is a field that is rapidly gaining attention due to its relevance to many autonomous agent applications. Providing demonstrations of effective behaviour to teach the agent is useful in real world challenges ...
  • Toward video tampering exposure: inferring compression parameters from pixels. 

    Johnston, Pamela; Elyan, Eyad; Jayne, Chrisina (Springer https://doi.org/10.1007/978-3-319-98204-5_4, 2018-07-27)
    JOHNSTON, P., ELYAN, E. and JAYNE, C. 2018. Toward video tampering exposure: inferring compression parameters from pixels. In Pimenidis, E. and Jayne, C. (eds.) Communications in computers and information science, 893: engineering applications of neural networks; proceedings of the 19th international engineering applications of neural networks conference (EANN 2018), 3-5 September 2018, Bristol, UK. Cham: Springer [online], pages 44-57. Available from: https://doi.org/10.1007/978-3-319-98204-5_4
    Video tampering detection remains an open problem in the field of digital media forensics. Some existing methods focus on recompression detection because any changes made to the pixels of a video will require recompression ...

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