Abstract
We present a method for the aggregation of qualitative preferences. This method is specially indicated when the set of criteria that is expressing the preferences is not homogeneous. That is, criteria have vocabularies with completely different terms, vocabularies with some common terms with different semantics or vocabularies with different granularity. The goal of the fusion process is to obtain a new ordered qualitative criterion expressing the overall preference over a set of alternatives. Our approach uses clustering techniques as an aggregation tool, and the principal components analysis to obtain a ranking of the alternatives.
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© 2002 Springer-Verlag Berlin Heidelberg
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Valls, A., Torra, V. (2002). Fusion of Qualitative Preferences with Different Vocabularies. In: Escrig, M.T., Toledo, F., Golobardes, E. (eds) Topics in Artificial Intelligence. CCIA 2002. Lecture Notes in Computer Science(), vol 2504. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36079-4_10
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DOI: https://doi.org/10.1007/3-540-36079-4_10
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