Abstract
The discovery of surprising relations in large, heterogeneous information repositories is gaining increasing importance in real world data analysis. If these repositories come from diverse origins, forming different domains, domain bridging associations between otherwise weakly connected domains can provide insights into the data that can otherwise not be accomplished. In this paper, we propose a first formalization for the detection of such potentially interesting, domain-crossing relations based purely on structural properties of a relational knowledge description.
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Nagel, U., Thiel, K., Kötter, T., Piątek, D., Berthold, M.R. (2011). Bisociative Discovery of Interesting Relations between Domains. 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_29
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DOI: https://doi.org/10.1007/978-3-642-24800-9_29
Publisher Name: Springer, Berlin, Heidelberg
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