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  From Black and White to Full Colour: Extending Redescription Mining Outside the Boolean World

Galbrun, E., & Miettinen, P. (2011). From Black and White to Full Colour: Extending Redescription Mining Outside the Boolean World. In Proceedings of the Eleventh SIAM International Conference on Data Mining (pp. 546-557). Philadelphia, PA: SIAM. Retrieved from http://siam.omnibooksonline.com/2011datamining/data/papers/275.pdf#page=1.

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 Urheber:
Galbrun, Esther1, Autor
Miettinen, Pauli2, Autor           
Affiliations:
1External Organizations, ou_persistent22              
2Databases and Information Systems, MPI for Informatics, Max Planck Society, ou_24018              

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Schlagwörter: -
 Zusammenfassung: Redescription mining is a powerful data analysis tool that is used to find multiple descriptions of the same entities. Consider geographical regions as an example. They can be characterized by the fauna that inhabits them on one hand and by their meteorological conditions on the other hand. Finding such redescriptors, a task known as niche-finding, is of much importance in biology. But current redescription mining methods cannot handle other than Boolean data. This restricts the range of possible applications or makes discretization a prerequisite, entailing a possibly harmful loss of information. In niche-finding, while the fauna can be naturally represented using a Boolean presence/absence data, the weather cannot. In this paper, we extend redescription mining to real-valued data using a surprisingly simple and efficient approach. We provide extensive experimental evaluation to study the behaviour of the proposed algorithm. Furthermore, we show the statistical significance of our results using recent innovations on randomization methods.

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Sprache(n): eng - English
 Datum: 20112011
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: eDoc: 618938
URI: http://siam.omnibooksonline.com/2011datamining/data/papers/275.pdf#page=1
Anderer: Local-ID: C1256DBF005F876D-9E2A2B3CCD413E07C125782900577857-galbrun10black
 Art des Abschluß: -

Veranstaltung

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Titel: Eleventh SIAM International Conference on Data Mining
Veranstaltungsort: Mesa, Arizona, USA
Start-/Enddatum: 2011-04-28 - 2011-04-30

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Titel: Proceedings of the Eleventh SIAM International Conference on Data Mining
Genre der Quelle: Konferenzband
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: Philadelphia, PA : SIAM
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 546 - 557 Identifikator: ISBN: 978-0-898719-92-5