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Learning Conditional Lexicographic Preference Trees

Bräuning, Michael; Hüllermeier, Eyke

Abstract:
We introduce a generalization of lexicographic orders and argue that this generalization constitutes an interesting model class for preference learning in general and ranking in particular. We propose a learning algorithm for inducing a so-called conditional lexicographic preference tree from a given set of training data in the form of pairwise comparisons between objects. Experimentally, we validate our algorithm in the setting of multipartite ranking.

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Volltext §
DOI: 10.5445/KSP/1000058747/03
Zugehörige Institution(en) am KIT Institut für Informationswirtschaft und Marketing (IISM)
Publikationstyp Zeitschriftenaufsatz
Jahr 2016
Sprache Englisch
Identifikator ISSN: 2363-9881
urn:nbn:de:swb:90-677616
KITopen-ID: 1000067761
Erschienen in Archives of Data Science, Series A
Band 1
Heft 1
Seiten 41-55
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