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Doctor Stewart Massie


Wifi-based human activity recognition using raspberry pi. (2020)
Conference Proceeding
FORBES, G., MASSIE, S. and CRAW, S. 2020. Wifi-based human activity recognition using raspberry pi. To be presented at 32nd International conference tools with artificial intelligence (ICTAI 2020), 9-11 November 2020, [virtual conference].

Ambient, non-intrusive approaches to smart home health monitoring, while limited in capability, are preferred by residents. More intrusive methods of sensing, such as video and wearables, can offer richer data but at the cost of lower resident uptake... Read More about Wifi-based human activity recognition using raspberry pi..

The folklore-centric gaze: a relational approach to landscape, folklore and tourism. (2020)
Journal Article
IRONSIDE, R. and MASSIE, S. [2020]. The folklore-centric gaze: a relational approach to landscape, folklore and tourism. Time and mind [online], Latest Articles. Available from: https://doi.org/10.1080/1751696X.2020.1809862

Supernatural folktales have a long oral tradition in Scotland, embedded in local communities and the landscapes of the region. Recently, these folktales have been utilised by destinations as a form of place-making, and a driver for increasing tourist... Read More about The folklore-centric gaze: a relational approach to landscape, folklore and tourism..

WEC: weighted ensemble of text classifiers. (2020)
Conference Proceeding
UPADHYAY, A., NGUYEN, T.T., MASSIE, S. and MCCALL, J. 2020. WEC: weighted ensemble of text classifiers. To be presented at the 2020 Institute of Electrical and Electronics Engineers (IEEE) congress on evolutionary computation (IEEE CEC 2020), part of the 2020 (IEEE) World congress on computational intelligence (IEEE WCCI 2020) and co-located with the 2020 International joint conference on neural networks (IJCNN 2020) and the 2020 IEEE International fuzzy systems conference (FUZZ-IEEE 2020), 18-24 July 2020, Glasgow, UK.

Text classification is one of the most important tasks in the field of Natural Language Processing. There are many approaches that focus on two main aspects: generating an effective representation; and selecting and refining algorithms to build the c... Read More about WEC: weighted ensemble of text classifiers..

Representing temporal dependencies in smart home activity recognition for health monitoring. (2020)
Conference Proceeding
FORBES, G., MASSIE, S., CRAW, S., FRASER, L. and HAMILTON, G. 2020. Representing temporal dependencies in smart home activity recognition for health monitoring. Presented at the 2020 Institute of Electrical and Electronics Engineers (IEEE) International joint conference on neural networks (IEEE IJCNN 2020), part of the 2020 IEEE World congress on computational intelligence (IEEE WCCI 2020) and co-located with the 2020 IEEE congress on evolutionary computation (IEEE CEC 2020) and the 2020 IEEE International fuzzy systems conference (FUZZ-IEEE 2020), 18-24 July 2020, [virtual conference].

Long term health conditions, such as fall risk, are traditionally diagnosed through testing performed in hospital environments. Smart Homes offer the opportunity to perform continuous, long-term behavioural and vitals monitoring of residents, which m... Read More about Representing temporal dependencies in smart home activity recognition for health monitoring..

Preface: case-based reasoning and deep learning. (2020)
Conference Proceeding
MARTIN, K., KAPETANAKIS, S., WIJEKOON, A., AMIN, K. and MASSIE, S. 2019. Preface: case-based reasoning and deep learning. In Kapetanakis, S. and Borck, H. (eds.) Proceedings of the 27th International conference on case-based reasoning workshop (ICCBR-WS19), co-located with the 27th International conference on case-based reasoning (ICCBR19), 8-12 September 2019, Otzenhausen, Germany. CEUR Workshop proceedings, 2567. Aachen: CEUR-WS [online], pages 6-7. Available from: http://ceur-ws.org/Vol-2567/cbr_dl_preface.pdf

Recent advances in deep learning (DL) have helped to usher in a new wave of confidence in the capability of artificial intelligence. Increasingly, we are seeing DL architectures out perform long established state-of-the-art algorithms in a numb... Read More about Preface: case-based reasoning and deep learning..

Representing temporal dependencies in human activity recognition. (2020)
Conference Proceeding
FORBES, G., MASSIE, S., CRAW, S., FRASER, L. and HAMILTON, G. 2019. Representing temporal dependencies in human activity recognition. In Kapetanakis, S. and Borck, H. (eds.) Proceedings of the 27th International conference on case-based reasoning workshop (ICCBR-WS19), co-located with the 27th International conference on case-based reasoning (ICCBR19), 8-12 September 2019, Otzenhausen, Germany. CEUR Workshop proceedings, 2567. Aachen: CEUR-WS [online], pages 29-38. Available from: http://ceur-ws.org/Vol-2567/paper3.pdf

Smart Homes offer the opportunity to perform continuous, long-term behavioural and vitals monitoring of residents, which may be employed to aid diagnosis and management of chronic conditions without placing additional strain on health services. A pro... Read More about Representing temporal dependencies in human activity recognition..

Representation and learning schemes for argument stance mining. (2019)
Thesis
CLOS, J. 2019. Representation and learning schemes for argument stance mining. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

Argumentation is a key part of human interaction. Used introspectively, it searches for the truth, by laying down argument for and against positions. As a mediation tool, it can be used to search for compromise between multiple human agents. For this... Read More about Representation and learning schemes for argument stance mining..

Ontology driven information retrieval. (2019)
Thesis
NKISI-ORJI, I. 2019. Ontology driven information retrieval. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

Ontology-driven information retrieval deals with the use of entities specified in domain ontologies to enhance search and browse. The entities or concepts of lightweight ontological resources are traditionally used to index resources in specialised d... Read More about Ontology driven information retrieval..

Fall prediction using behavioural modelling from sensor data in smart homes. (2019)
Journal Article
FORBES, G., MASSIE, S. and CRAW, S. 2020. Fall prediction using behavioural modelling from sensor data in smart homes. Artificial intelligence review [online], 53(2), pages 1071-1091. 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 laboratory environments, however... Read More about Fall prediction using behavioural modelling from sensor data in smart homes..

Ontology alignment based on word embedding and random forest classification. (2019)
Conference Proceeding
NKISI-ORJI, I., WIRATUNGA, N., MASSIE, S., HUI, K.-Y. and HEAVEN, R. 2019. Ontology alignment based on word embedding and random forest classification. In Berlingerio, M., Bonchi, F., Gärtner, T., Hurley, N. and Ifrim, G. (eds.) Machine learning and knowledge discovery in databases: proceedings of the 2018 European conference on machine learning and principles and practice of knowledge discovery in databases (ECML PKDD 2018), 10-14 September 2018, Dublin, Ireland. Lecture notes in computer science, 11051. Cham: Springer [online], part I, pages 557-572. Available from: https://doi.org/10.1007/978-3-030-10925-7_34

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 and used for discovering corr... Read More about Ontology alignment based on word embedding and random forest classification..

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