Esther Dopazo

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The pairwise comparison method is an interesting technique for building a global ranking from binary comparisons. In fact, some web search engines use this method to quantify the importance of a set of web sites. The purpose of this paper is to search a set of priority weights from the preference information contained in a general pairwise comparison(More)
Fuzzy decision-making: Consensus and Missing preferences Abstract—City-rankings have become a central instrument for assessing the attractiveness of urban regions over the last years. Demographic, environmental, economic, political and socio-cultural factors are forcing the urban world to design and implement Smart Cities. A set of multidimensional(More)
Preference learning has recently received a lot of attention within the machine learning field, concretely learning by pairwise comparisons is a well-established technique in this field. We focus on the problem of learning the overall preference weights of a set of alternatives from the (possibly conflicting) uncertain and imprecise information given by a(More)
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