Publikation: Bisociative Discovery of Interesting Relations between Domains
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2011
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GAMA, João, ed., Elizabeth BRADLEY, ed., Jaakko HOLLMÉN, ed.. Advances in Intelligent Data Analysis X. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, pp. 306-317. Lecture Notes in Computer Science. 7014. ISBN 978-3-642-24799-6. Available under: doi: 10.1007/978-3-642-24800-9_29
Zusammenfassung
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, Uwe, Kilian THIEL, Tobias KÖTTER, Dawid PIATEK, Michael R. BERTHOLD, 2011. Bisociative Discovery of Interesting Relations between Domains. In: GAMA, João, ed., Elizabeth BRADLEY, ed., Jaakko HOLLMÉN, ed.. Advances in Intelligent Data Analysis X. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, pp. 306-317. Lecture Notes in Computer Science. 7014. ISBN 978-3-642-24799-6. Available under: doi: 10.1007/978-3-642-24800-9_29BibTex
@inproceedings{Nagel2011Bisoc-18006,
year={2011},
doi={10.1007/978-3-642-24800-9_29},
title={Bisociative Discovery of Interesting Relations between Domains},
number={7014},
isbn={978-3-642-24799-6},
publisher={Springer Berlin Heidelberg},
address={Berlin, Heidelberg},
series={Lecture Notes in Computer Science},
booktitle={Advances in Intelligent Data Analysis X},
pages={306--317},
editor={Gama, João and Bradley, Elizabeth and Hollmén, Jaakko},
author={Nagel, Uwe and Thiel, Kilian and Kötter, Tobias and Piatek, Dawid and Berthold, Michael R.}
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<dcterms:abstract xml:lang="eng">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.</dcterms:abstract>
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<dcterms:bibliographicCitation>10th international symposium, IDA 2011, Porto, Portugal, October 29 - 31, 2011; proceedings / João Gama ... (eds.). - Berlin; Heidelberg : Springer, 2011. - S. 306-317. - (Advances in intelligent data analysis ; 10 und Lecture notes in computer science ; 7014). - ISBN 978-3-642-24799-6</dcterms:bibliographicCitation>
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