Abstract
In several situations, a set of objects must be positioned based on the preferences of a set of individuals. Sometimes, each individual can/does only include a limited subset of objects in his preferences (partial preferences). We present an approach whereby a matrix of distances between objects can be derived based on the partial preferences expressed by individuals on those objects. In this way, the similarities and differences between the various objects can subsequently be analyzed. A graphical representation of objects can also be obtained from the distance matrix using classical multivariate techniques such as hierarchical classification and multidimensional scaling.
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Mateo-Sanz, J.M., Domingo-Ferrer, J., Torra, V. (2004). Object Positioning Based on Partial Preferences. In: Torra, V., Narukawa, Y. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2004. Lecture Notes in Computer Science(), vol 3131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27774-3_24
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DOI: https://doi.org/10.1007/978-3-540-27774-3_24
Publisher Name: Springer, Berlin, Heidelberg
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