All Outputs (23)

Harnessing background knowledge for e-learning recommendation.
Presentation / Conference Contribution
MBIPOM, B., CRAW, S. and MASSIE, S. 2016. Harnessing background knowledge for e-learning recommendation. 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 (SGAI 2016), 13-15 December 2016, Cambridge, UK. Cham: Springer [online], pages 3-17. Available from: https://dx.doi.org/10.1007/978-3-319-47175-4_1

The growing availability of good quality, learning-focused content on the Web makes it an excellent source of resources for e-learning systems. However, learners can find it hard to retrieve material well-aligned with their learning goals because of... Read More about Harnessing background knowledge for e-learning recommendation..

Music recommendation: audio neighbourhoods to discover music in the long tail.
Presentation / Conference Contribution
CRAW, S., HORSBURGH, B. and MASSIE, S. 2015. Music recommendation: audio neighbourhoods to discover music in the long tail. In Hüllermeier, E. and Minor, M. (eds.) Proceedings of the 23rd international conference on case-based reasoning research and development (ICCBR 2015), 28-30 September 2015, Frankfurt am Main, Germany. Lecture notes in computer science, 9343. Cham: Springer [online], pages 73-87. Available from: https://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 that they do not already... Read More about Music recommendation: audio neighbourhoods to discover music in the long tail..

Visualisation to explain personal health trends in smart homes.
Presentation / Conference Contribution
FORBES, G., MASSIE, S. and CRAW, S. 2021. Visualisation to explain personal health trends in smart homes. Presented at 1st eXplainable artificial intelligence (XAI) in healthcare international workshop 2021 (XAI-Healthcare 2021), 16 June 2021, co-located with 19th Artificial intelligence in medicine (AIME) international conference 2021 (AIME 2021), 15-17 June 2021, [virtual conference]. Hosted on ArXiv [online], article 2109.15125. Available from: https://arxiv.org/abs/2109.15125

An ambient sensor network is installed in Smart Homes to identify low-level events taking place by residents, which are then analysed to generate a profile of activities of daily living. These profiles are compared to both the resident's typical prof... Read More about Visualisation to explain personal health trends in smart homes..