Preference learning is a challenging problem that involves the prediction of complex structures, such as weak or partial order relations. In the recent literature, the problem appears in many different guises, which we will first put into a coherent framework. This work then focuses on a particular learning scenario called label ranking, where the problem is to learn a mapping from instances to...

Research from behavioral psychology and experimental economics asserts that individuals construct preferences on a case-by-case basis when called to make a decision. A common, implicit assumption in engineering design is that user preferences exist a priori. Thus, preference elicitation methods used in design decision making can lead to preference inconsistencies across elicitation scenarios. T...

We study the task of learning the preferences of online readers of news, based on their past choices. Previous work has shown that it is possible to model this situation as a competition between articles, where the most appealing articles of the day are those selected by the most users. The appeal of an article can be computed from its textual content, and the evaluation function can be learned...

This paper is devoted to construction of fuzzy preference relations and to showing how this construction is connected with Lukasiewicz filters and TL-evaluators. We will study also extensions of Lukasiewicz filters on subsets of some X 6= ∅ to TL-evaluators on the system (lattice) of fuzzy functions f : X → [0, 1].

In decision making, in order to avoid misleading solutions, the study of consistency when the decision makers express their opinions by means of preference relations becomes a very important aspect in order to avoid misleading solutions. In decision making problems based on fuzzy preference relations the study of consistency is associated with the study of the transitivity property. In this pap...

Electronic markets are based on classic market design assumptions that often do not hold. This thesis examines the conflict between theory and practice for the class of Vickrey-Clarke-Groves mechanisms (VCG) and the auctions it has inspired in electronic commerce, most notably the iterative auctions found on eBay. VCG mechanisms provide bidders with an optimal strategy to truthfully reveal thei...

Group decision is usually understood as the reduction of different individual preferences on a given set to a single collective preference. At present, there are few approaches which solve the group ranking problem with multiple criteria in a widely acceptable way. Often, they rest on a poor heuristic which makes a decision about consensus ranking difficult to support. This paper presents an ex...

Preference learning is a challenging problem that involves the prediction of complex structures, such as weak or partial order relations, rather than single values. In the recent literature, the problem appears in many different guises, which we will first put into a coherent framework. This work then focuses on a particular learning scenario called label ranking, where the problem is to learn ...

We have measured oxygen wash-in in 20 volunteers undergoing preoxygenation with a face mask, mouthpiece alone and a mouthpiece with a noseclip, in a crossover study. Tidal volume breathing and maximal deep breath techniques were studied with each type of equipment. When tidal volume breathing was used, the face mask and mouthpiece with noseclip were comparable, but the mouthpiece alone achieved...

In this paper, we present an approach for predicting users’ level of engagement from nonverbal cues within a game environment. We use a data corpus collected from 28 participants (152 minutes of video recording) playing the popular platform game Super Mario Bros. The richness of the corpus allows extraction of several visual and facial expression features that were utilised as indicators of pla...