Professor Susan Craw's Outputs (7)

Case based reasoning as a model for cognitive artificial intelligence. (2018)
Presentation / Conference Contribution
CRAW, S. and AAMODT, A. 2018. Case based reasoning as a model for cognitive artificial intelligence. In Cox, M.T., Funk, P. and Begum, S. (eds.) Case-based reasoning research and development: proceedings of the 26th International conference on case-based reasoning (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Lecture notes in computer science, 11156. Cham: Springer [online], pages 62-77. Available from: https://doi.org/10.1007/978-3-030-01081-2_5

Cognitive Systems understand the world through learning and experience. Case Based Reasoning (CBR) systems naturally capture knowledge as experiences in memory and they are able to learn new experiences to retain in their memory. CBR's retrieve and r... Read More about Case based reasoning as a model for cognitive artificial intelligence..

FITsense: employing multi-modal sensors in smart homes to predict falls. (2018)
Presentation / Conference Contribution
MASSIE, S., FORBES, G., CRAW, S., FRASER, L. and HAMILTON, G. 2018. FITsense: employing multi-modal sensors in smart homes to predict falls. In Cox, M.T., Funk, P. and Begum, S. (eds.) Case-based reasoning research and development: proceedings of the 26th International conference on case-based reasoning (ICCBR 2018), 9-12 July 2018, Stockholm, Sweden. Lecture notes in computer science, 11156. Cham: Springer [online], pages 249-263. Available from: https://doi.org/10.1007/978-3-030-01081-2_17

As people live longer, the increasing average age of the population places additional strains on our health and social services. There are widely recognised benefits to both the individual and society from supporting people to live independently for... Read More about FITsense: employing multi-modal sensors in smart homes to predict falls..

Maintenance of case bases: current algorithms after fifty years. (2018)
Presentation / Conference Contribution
JUAREZ, J.M., CRAW, S., LOPEZ-DELGADO, J.R. and CAMPOS, M. 2018. Maintenance of case bases: current algorithms after fifty years. In Lang, J. (ed.) Proceedings of the 27th International joint conference on artificial intelligence and the 23rd European conference on artificial intelligence (IJCAI-ECAI 2018), 13-19 July 2018, Stockholm, Sweden. Freiburg: IJCAI [online], pages 5457-5463. Available from: https://doi.org/10.24963/ijcai.2018/770

Case-Based Reasoning (CBR) learns new knowledge from data and so can cope with changing environments. CBR is very different from modelbased systems since it can learn incrementally as new data is available, storing new cases in its casebase. This mea... Read More about Maintenance of case bases: current algorithms after fifty years..

Monitoring health in smart homes using simple sensors. (2018)
Presentation / Conference Contribution
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 (KDH), 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. CEUR workshop proceedings, 2148. Aachen: CEUR-WS [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 profiles are compared to bot... Read More about Monitoring health in smart homes using simple sensors..

Knowledge driven approaches to e-learning recommendation. (2018)
Thesis
MBIPOM, B. 2018. Knowledge driven approaches to e-learning recommendation. Robert Gordon University, PhD thesis.

Learners often have difficulty finding and retrieving relevant learning materials to support their learning goals because of two main challenges. The vocabulary learners use to describe their goals is different from that used by domain experts in tea... Read More about Knowledge driven approaches to e-learning recommendation..

An e-learning recommender that helps learners find the right materials. (2018)
Presentation / Conference Contribution
MBIPO, B., MASSIE, S. and CRAW, S. 2018. An e-learning recommender that helps learners find the right materials. In Zilberstein, S., McIlraith, S., Weinberger, K., Youngblood, G.M., Myers, K., Eaton, E. and Wollowski, M. (eds.) Proceedings of the 32nd Association for the Advancement of Artificial Intelligence (AAAI) Artificial intelligence conference (AAAI18), co-located with the 30th Innovative applications of artificial intelligence conference (IAAI18) and the 8th AAAI Educational advances in artificial intelligence (EAAI-18), 2-7 February 2018, New Orleans, Louisiana, USA. Palo Alto: AAAI Press [online], pages 7928-7933. Available from: https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16253

Learning materials are increasingly available on the Web making them an excellent source of information for building e-Learning recommendation systems. However, learners often have difficulty finding the right materials to support their learning goal... Read More about An e-learning recommender that helps learners find the right materials..

Improving e-learning recommendation by using background knowledge. (2018)
Journal Article
MBIPOM, B., CRAW, S. and MASSIE, S. 2021. Improving e-learning recommendation by using background knowledge. Expert systems [online], 38(7): artificial intelligence/EDMA 2017, article e12265. Available from: https://doi.org/10.1111/exsy.12265

There is currently a large amount of e-Learning resources available to learners on the Web. However, learners often have difficulty finding and retrieving relevant materials to support their learning goals because they lack the domain knowledge to cr... Read More about Improving e-learning recommendation by using background knowledge..