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- W2514036619 abstract "We suppose that all we know about the preferences of an agent, is given by a (small) collection of relative preferences between choices represented by their evaluations on a set of criteria. Taking lesson from the success of the use of analogical proportions for predicting the class of a new item from a set of classified examples, we explore the possibility of using analogical proportions for completing a set of relative preferences. Such an approach is also motivated by a striking similarity between the formal structure of the axiomatic characterization of weighted averages and the logical definition of an analogical proportion. This paper discusses how to apply an analogical proportion-based approach to the learning of relative preferences, assuming that the preferences are representable by a weighted average, and how to validate experimental results. The approach is illustrated by examples." @default.
- W2514036619 created "2016-09-16" @default.
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- W2514036619 date "2016-01-01" @default.
- W2514036619 modified "2023-10-16" @default.
- W2514036619 title "Completing Preferences by Means of Analogical Proportions" @default.
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- W2514036619 doi "https://doi.org/10.1007/978-3-319-45656-0_12" @default.
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