Dr David Corsar's Outputs (33)

Demystifying the black box: the importance of interpretability of predictive models in neurocritical care. (2022)
Journal Article
MOSS, L., CORSAR, D., SHAW, M., PIPER, I. and HAWTHORNE, C. 2022. Demystifying the black box: the importance of interpretability of predictive models in neurocritical care. Neurocritical care [online], 37(Supplement 2): big data in neurocritical care, pages 185-191. Available from: https://doi.org/10.1007/s12028-022-01504-4

Neurocritical care patients are a complex patient population, and to aid clinical decision-making, many models and scoring systems have previously been developed. More recently, techniques from the field of machine learning have been applied to neuro... Read More about Demystifying the black box: the importance of interpretability of predictive models in neurocritical care..

DisCERN: discovering counterfactual explanations using relevance features from neighbourhoods. (2021)
Presentation / Conference Contribution
WIRATUNGA, N., WIJEKOON, A., NKISI-ORJI, I., MARTIN, K., PALIHAWADANA, C. and CORSAR, D. 2021. DisCERN: discovering counterfactual explanations using relevance features from neighbourhoods. In Proceedings of 33rd IEEE (Institute of Electrical and Electronics Engineers) International conference on tools with artificial intelligence 2021 (ICTAI 2021), 1-3 November 2021, Washington, USA [virtual conference]. Piscataway: IEEE [online], pages 1466-1473. Available from: https://doi.org/10.1109/ICTAI52525.2021.00233

Counterfactual explanations focus on 'actionable knowledge' to help end-users understand how a machine learning outcome could be changed to a more desirable outcome. For this purpose a counterfactual explainer needs to discover input dependencies tha... Read More about DisCERN: discovering counterfactual explanations using relevance features from neighbourhoods..

Actionable feature discovery in counterfactuals using feature relevance explainers. (2021)
Presentation / Conference Contribution
WIRATUNGA, N., WIJEKOON, A., NKISI-ORJI, I., MARTIN, K., PALIHAWADANA, C. and CORSAR, D. 2021. Actionable feature discovery in counterfactuals using feature relevance explainers. In Borck, H., Eisenstadt, V., Sánchez-Ruiz, A. and Floyd, M. (eds.) Workshop proceedings of the 29th International conference on case-based reasoning (ICCBR-WS 2021), 13-16 September 2021, [virtual event]. CEUR workshop proceedings, 3017. Aachen: CEUR-WS [online], pages 63-74. Available from: http://ceur-ws.org/Vol-3017/101.pdf

Counterfactual explanations focus on 'actionable knowledge' to help end-users understand how a Machine Learning model outcome could be changed to a more desirable outcome. For this purpose a counterfactual explainer needs to be able to reason with si... Read More about Actionable feature discovery in counterfactuals using feature relevance explainers..

Counterfactual explanations for student outcome prediction with Moodle footprints. (2021)
Presentation / Conference Contribution
WIJEKOON, A., WIRATUNGA, N., NKILSI-ORJI, I., MARTIN, K., PALIHAWADANA, C. and CORSAR, D. 2021. Counterfactual explanations for student outcome prediction with Moodle footprints. In Martin, K., Wiratunga, N. and Wijekoon, A. (eds.) SICSA XAI workshop 2021: proceedings of 2021 SICSA (Scottish Informatics and Computer Science Alliance) eXplainable artificial intelligence workshop (SICSA XAI 2021), 1st June 2021, [virtual conference]. CEUR workshop proceedings, 2894. Aachen: CEUR-WS [online], session 1, pages 1-8. Available from: http://ceur-ws.org/Vol-2894/short1.pdf

Counterfactual explanations focus on “actionable knowledge” to help end-users understand how a machine learning outcome could be changed to one that is more desirable. For this purpose a counterfactual explainer needs to be able to reason with simila... Read More about Counterfactual explanations for student outcome prediction with Moodle footprints..

Ensemble-based relationship discovery in relational databases. (2020)
Presentation / Conference Contribution
OGUNSEMI, A., MCCALL, J., KERN, M., LACROIX, B., CORSAR, D. and OWUSU, G. 2020. Ensemble-based relationship discovery in relational databases. In Bramer, M. and Ellis, R. (eds.) Artificial intelligence XXXVII: proceedings of 40th British Computer Society's Specialist Group on Artificial Intelligence (SGAI) Artificial intelligence international conference 2020 (AI-2020), 15-17 December 2020, [virtual conference]. Lecture notes in artificial intelligence, 12498. Cham: Springer [online], pages 286-300. Available from: https://doi.org/10.1007/978-3-030-63799-6_22

We performed an investigation of how several data relationship discovery algorithms can be combined to improve performance. We investigated eight relationship discovery algorithms like Cosine similarity, Soundex similarity, Name similarity, Value ran... Read More about Ensemble-based relationship discovery in relational databases..

Clood CBR: towards microservices oriented case-based reasoning. (2020)
Presentation / Conference Contribution
NKISI-ORJI, I., WIRATUNGA, N., PALIHAWADANA, C., RECIO-GARCIA, J.A. and CORSAR, D. 2020. Clood CBR: towards microservices oriented case-based reasoning. In Watson, I and Weber, R. (eds.) Case-based reasoning research and development: proceedings of the 28th International conference on case-based reasoning research and development (ICCBR 2020), 8-12 June 2020, Salamanca, Spain [virtual conference]. Lecture notes in computer science, 12311. Cham: Springer [online], pages 129-143. Available from: https://doi.org/10.1007/978-3-030-58342-2_9

CBR applications have been deployed in a wide range of sectors, from pharmaceuticals; to defence and aerospace to IoT and transportation, to poetry and music generation; for example. However, a majority of these have been built using monolithic archi... Read More about Clood CBR: towards microservices oriented case-based reasoning..

Made-up rubbish: design fiction as a tool for participatory Internet of Things research. (2020)
Journal Article
JACOBS, N., MARKOVIC, M., COTTRILL, C.D., EDWARDS, P., CORSAR, D. and SALT, K. 2020. Made-up rubbish, design fiction as a tool for participatory Internet of Things research. Design journal [online], 23(3), pages 419-440. Available from: https://doi.org/10.1080/14606925.2020.1744259

As Internet of Things (IoT) technologies become embedded in public infrastructure, it is important that we consider how they may introduce new challenges in areas such as privacy and governance. Public technology implementations can be more democrati... Read More about Made-up rubbish: design fiction as a tool for participatory Internet of Things research..

Learning to self-manage by intelligent monitoring, prediction and intervention. (2019)
Presentation / Conference Contribution
WIRATUNGA, N., CORSAR, D., MARTIN, K., WIJEKOON, A., ELYAN, E., COOPER, K., IBRAHIM, Z., CELIKTUTAN, O., DOBSON, R.J., MCKENNA, S., MORRIS, J., WALLER, A., ABD-ALHAMMED, R., QAHWAJI, R. and CHAUDHURI, R. 2019. Learning to self-manage by intelligent monitoring, prediction and intervention. In Wiratunga, N., Coenen, F. and Sani, S. (eds.) Proceedings of the 4th International workshop on knowledge discovery in healthcare data (KDH 2019), co-located with the 28th International joint conference on artificial intelligence (IJCAI-19), 10-11 August 2019, Macao, China. CEUR workshop proceedings, 2429. Aachen: CEUR-WS [online], pages 60-67. Available from: http://ceur-ws.org/Vol-2429/paper10.pdf

Despite the growing prevalence of multimorbidities, current digital self-management approaches still prioritise single conditions. The future of out-of-hospital care requires researchers to expand their horizons; integrated assistive technologies sho... Read More about Learning to self-manage by intelligent monitoring, prediction and intervention..

Understanding factors influencing public transport passengers' pre-travel information-seeking behaviour. (2019)
Journal Article
YEBOAH, G., COTTRILL, C.D., NELSON, J.D., CORSAR, D., MARKOVIC, M. and EDWARDS, P. 2019. Understanding factors influencing public transport passengers’ pre-travel information-seeking behaviour. Public transport [online], 11(1), pages 135-158. Available from: https://doi.org/10.1007/s12469-019-00198-w

This paper investigates factors influencing public transport passengers’ pre-travel information-seeking behaviours in a British urban environment. Public transport traveller surveys were conducted to better understand the journey stages at which info... Read More about Understanding factors influencing public transport passengers' pre-travel information-seeking behaviour..

Minimality and simplicity of rules for the internet-of-things. (2019)
Presentation / Conference Contribution
PANARETOS, A., CORSAR, D. and VASCONCELOS, W.W. 2019. Minimality and simplicity of rules for the internet-of things. In Lujak, M. (ed.) Agreement technologies: revised selected papers from the 6th International conference on agreement technologies (AT 2018), 6-7 December 2018, Bergen, Norway. Lecture notes in computer science, 11327. Cham: Springer [online], pages 64-72. Available from: https://doi.org/10.1007/978-3-030-17294-7_5

Rule-based systems have been increasing in popularity in recent years. They allow for easier handling of both simple and complicated problems utilising a set of rules created in various ways (e.g., manually, or (semi-) automatically, via, say, machin... Read More about Minimality and simplicity of rules for the internet-of-things..

Challenges of open data quality: more than just license, format, and customer support. (2017)
Journal Article
CORSAR, D. and EDWARDS, P. 2017. Challenges of open data quality: more than just license, format, an customer support. Journal of data and information quality [online], 9(1), pages 1-4. Available from: https://doi.org/10.1145/3139489

Public sector organisations worldwide are implementing Open Data initiatives, which, it is hoped, will stimulate economic growth, increase transparency and accountability, and improve engagement between data consumers (typically citizens) and data ho... Read More about Challenges of open data quality: more than just license, format, and customer support..

Linking open data and the crowd for real-time passenger information. (2017)
Journal Article
CORSAR, D., EDWARDS, P., NELSON, J., BAILLIE, C., PAPANGELIS, K. and VELAGA, N. 2017. Linking open data and the crowd for real-time passenger information. Journal of web semantics [online], 43, pages 18-24. Available from: https://doi.org/10.1016/j.websem.2017.02.002

The availability of real-time passenger information (RTPI) is a key factor in making public transport both accessible and attractive to users. Unfortunately, rural areas often lack the infrastructure necessary to provide such information, and the cos... Read More about Linking open data and the crowd for real-time passenger information..

The transport disruption ontology. (2015)
Presentation / Conference Contribution
CORSAR, D., MARKOVIC, M., EDWARDS, P. and NELSON, J.D. 2015. The transport disruption ontology. In Arenas, M., Corcho, O., Simperl, E., Strohmaier, M., d'Aquin, M., Srinivas, K., Groth, P., Dumontier, M., Heflin, J., Thirunarayan, K. and Staab, S. (eds.). The sematic web - ISWC 2015: proceedings of the 14th International semantic web conference 2015 (ISWC 2015), 11-15 October 2015, Bethleham, PA, USA, 9367. Lecture notes in computer science. Cham: Springer [online], pages 329-336. Available from: https://doi.org/10.1007/978-3-319-25010-6_22

This paper presents the Transport Disruption ontology, a formal framework for modelling travel and transport related events that have a disruptive impact on traveller's journeys. We discuss related models , describe how transport events and their imp... Read More about The transport disruption ontology..