Abstract
Data analysis generally focusses on finding patterns within a reasonably well connected domain of interest. In this article we focus on the discovery of new connections between domains (so called bisociations), supporting the creative discovery process in a novel way. We motivate this approach, show the difference to classical data analysis and conclude by briefly illustrating some types of domain-crossing connections along with illustrative examples.
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References
Berthold, M.R. (ed.): Bisociative Knowledge Discovery, 1st edn. LNCS. Springer, Heidelberg (in preparation)
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© 2011 Springer-Verlag Berlin Heidelberg
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Berthold, M.R. (2011). Bisociative Knowledge Discovery. In: Gama, J., Bradley, E., Hollmén, J. (eds) Advances in Intelligent Data Analysis X. IDA 2011. Lecture Notes in Computer Science, vol 7014. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24800-9_1
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DOI: https://doi.org/10.1007/978-3-642-24800-9_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24799-6
Online ISBN: 978-3-642-24800-9
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