Abstract
In the past, the development of machine learning approaches was to some extent motivated by the availability of data and increased computational power. Ubiquitous computing bears the promise of stimulating a similar leap forward. Small devices can now be installed in many places, mobile and wearable devices enable registration of large amounts of information, thus generating a wide range of new types of data for which new learning and discovery methods are needed, far beyond existing ones.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Liao, L., Patterson, D.J., Fox, D., Kautz, H.: Learning and inferring transportation routines. Artif. Intell. 171(5-6), 311–331 (2007)
Kargupta, H., Bhargava, R., Liu, K., Powers, M., Blair, P., Bushra, S., Dull, J., Sarkar, K., Klein, M., Vasa, M., Handy, D.: Vedas: A mobile and distributed data stream mining system for real-time vehicle monitoring. In: Proceedings of the SIAM International Data Mining Conference, Orlando (2004)
May, M., Berendt, B., Cornéjols, A., Gama, J., Gianotti, F., Hotho, A., Malerba, D., Menesalvas, E., Morik, K., Pedersen, R., Saitta, L., Saygin, Y., Schuster, A., Vanhoof, K.: Research challenges in ubiquitous knowledge discovery. In: Kargupta, H., Han, J., Yu, P.S., Motwani, R., Kumar, V. (eds.) Next Generation of Data Mining, ch. 7, pp. 131–150. Chapman & Hall/CRC (2008)
Mierswa, I., Morik, K., Wurst, M.: Collaborative use of features in a distributed system for the organization of music collections. In: Shen, S., Cui, L. (eds.) Intelligent Music Information Systems: Tools and Methodologies, pp. 147–176. Idea Group Publishing, USA (2007)
Flasch, O., Kaspari, A., Morik, K., Wurst, M.: Aspect-based tagging for collaborative media organisation. In: Proceedings of the ECML/PKDD workshop on Ubiquitous Knowledge Discovery for Users (2006)
Wurst, M., Morik, K.: Distributed feature extraction in a p2p setting - a case study. In: Future Generation Computer Systems, Special Issue on Data Mining (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
May, M., Saitta, L. (2010). Introduction: The Challenge of Ubiquitous Knowledge Discovery. In: May, M., Saitta, L. (eds) Ubiquitous Knowledge Discovery. Lecture Notes in Computer Science(), vol 6202. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16392-0_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-16392-0_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16391-3
Online ISBN: 978-3-642-16392-0
eBook Packages: Computer ScienceComputer Science (R0)