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G. Tsoumakas, E. Loza Mencia, I. Katakis, S. Park, J. Furnkrnaz, “On the combination of two decompositive multi-label classification methods”, Workshop on Preference Learning, ECML PKDD 09, Eyke Hullermeir, Johannes Furnkranz (Ed.), pp. 114-133, Bled, Slovenia, 2009.
