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Cited by 19 publications
(9 citation statements)
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“…In all these cases, each piece of collected information then helps to better identify the preference model of the DM. Also, the elicitation processes may differ greatly between the different MCDA models, be it Choquet Integrals [28], GAI-networks [27], CP-net [6], lexicographic orderings [26,22] and their conditional extensions [4], . .…”
Section: Introductionmentioning
confidence: 99%
“…In all these cases, each piece of collected information then helps to better identify the preference model of the DM. Also, the elicitation processes may differ greatly between the different MCDA models, be it Choquet Integrals [28], GAI-networks [27], CP-net [6], lexicographic orderings [26,22] and their conditional extensions [4], . .…”
Section: Introductionmentioning
confidence: 99%
“…In fact, the most studied model up to now is lexicographic preferences for binary attributes. The problem is first addressed in [14], which investigate several problems regarding learning lexicographical preference relations. First they give a polynomial-time algorithm which, from a set of pairwise comparisons between vectors of values, determines the importance order of the criteria if it is possible, or decides whether the sample is insufficient or inconsistent.…”
Section: Introductionmentioning
confidence: 99%
“…This area is often also referred to as preference elicitation (Haddawy et al 2003;Bonilla et al 2010). An alternative line of research investigates special types of preference models such as outranking relations (Greco et al 2011), rough set-based decision rules (Greco et al 2001), lexicographic orders (Dombi et al 2007;Schmitt and Martignon 2006;Flach and Matsubara 2007;Yaman et al 2011) and CP-nets (Boutilier et al 2004). Popular application areas include collaborative filtering, where a customer's preferences are estimated from the preferences of other customers (Breese et al 1998;Sarwar et al 2001), and personalized ranking techniques for information retrieval (Radlinski and Joachims 2005;Radlinski et al 2011;Rudin 2009).…”
mentioning
confidence: 99%