Summary
Ambient Intelligence environments depend on their capability to learn user’s preferences and typical behavior. In this paper we present an algorithm that taking as starting point information collected by sensors finds out accurate temporal relations among actions carried out by the user.
Keywords
- Ambient Intelligence
- Context Aware Computing
- Learning behavioral patterns
- Temporal relations
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References
Allen, J.: Towards a general theory of action and time. Artificial Intelligence 23, 123–154 (1984)
Augusto, J.C.: Ambient Intelligence: the Confluence of Ubiquitous/Pervasive Computing and Artificial Intelligence. In: Intelligent Computing Everywhere, pp. 213–234. Springer, London (2007)
Augusto, J.C., Cook, D.J.: Ambient intelligence: applications in society and opportunities for ai. In: 20th International Joint Conference on Artificial Intelligence (IJCAI 2007) (2007)
Augusto, J.C., Nugent, C.D.: The use of temporal reasoning and management of complex events in smart homes (2004)
Aztiria, A., Augusto, J.C., Izaguirre, A.: Spatial and temporal aspects for pattern representation and discovery in intelligent environments. In: Workshop on Spatial and Temporal Reasoning at 18th European Conference on Artificial Intelligence (ECAI 2008) (to published, 2008)
Begg, R., Hassan, R.: Artificial neural networks in smart homes. In: Designing Smart Homes. The Role of Artificial Intelligence, pp. 146–164. Springer, Heidelberg (2006)
Cook, D.J., Das, S.K.: Smart Environments: Technology, Protocols and Applications. Wiley-Interscience, Chichester (2005)
Cook, D.J., Huber, M., Gopalratnam, K., Youngblood, M.: Learning to control a smart home environment. In: Innovative Applications of Artificial Intelligence (2003)
Le Gal, C., Martin, J., Lux, A., Crowley, J.L.: Smartoffice: Design of an intelligent environment. IEEE Intelligent Systems 16(4), 60–66 (2001)
Hagras, H., Callaghan, V., Colley, M., Clarke, G., Pounds-Cornish, A., Duman, H.: Creating an ambient-intelligence environment using embedded agents. IEEE Intelligent Systems 19(6), 12–20 (2004)
Jakkula, V.R., Cook, D.J.: Using temporal relations in smart environment data for activity prediction. In: Proceedings of the 24th International Conference on Machine Learning (2007)
Muller, M.E.: Can user models be learned at all? inherent problems in machine learning for user modelling. In: Knowledge Engineering Review, vol. 19, pp. 61–88. Cambridge University Press, Cambridge (2004)
Sadeh, N.M., Gandom, F.L., Kwon, O.B.: Ambient intelligence: The mycampus experience. Technical Report CMU-ISRI-05-123, ISRI (2005)
Weiser, M.: The computer for the 21st century. Scientific American 265(3), 94–104 (1991)
Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. Elsevier, Amsterdam (2005)
Youngblood, G.M., Cook, D.J., Holder, L.B.: Managing adaptive versatile environments. In: IEEE International Conference on Pervasive Computing and Communications (2005)
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© 2009 Springer-Verlag Berlin Heidelberg
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Aztiria, A., Augusto, J.C., Izaguirre, A., Cook, D. (2009). Learning Accurate Temporal Relations from User Actions in Intelligent Environments. In: Corchado, J.M., Tapia, D.I., Bravo, J. (eds) 3rd Symposium of Ubiquitous Computing and Ambient Intelligence 2008. Advances in Soft Computing, vol 51. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85867-6_32
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DOI: https://doi.org/10.1007/978-3-540-85867-6_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85866-9
Online ISBN: 978-3-540-85867-6
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