Common approaches to product recommendations are offer level propensity models and collaborative filtering. These methods are typically used for respectively a low or a high number of products, and come with specific limitations. In this paper we introduce preference based approaches to product recommendations, aimed at filling the gap between these methods. This approach can be used for any ex...

User’s choices involve habitual behavior and genuine decisions. Habitual behavior is often represented using preferences. The conditional preference network (CP-net) is a graphical tool for representing and reasoning about conditional preferences. We argue that genuine decisions are environmentally influenced and we introduce the notion of “comfort” to represent this type of choices. In this pa...

Studying color preferences provides a means to discover how perceptual experiences map onto cognitive and affective judgments. A challenge is finding a parsimonious way to describe and predict patterns of color preferences, which are complex with rich individual differences. One approach has been to model color preferences using factors from metric color spaces to establish direct correspondenc...

The use of possibilistic networks for representing conditional preference statements on discrete variables has been proposed only recently. The approach uses non-instantiated possibility weights to define conditional preference tables. Moreover, additional information about the relative strengths of these symbolic weights can be taken into account. The fact that at best we have some information...

The value of travel time savings (VTTS) is the monetary value attached to save a determined amount of travel time. VTTS is also the most important benefit category aimed at justifying investments in transport infrastructures by public administrations. Hence VTTS played a significant role in various economic studies, both analytical and empirical (Zamparini & Reggiani, 2007). "It is difficult to...

The incorporation of plastic and adaptive user-interfaces into the model-based paradigm requires a new, more flexible modeling formalism. Rather than modeling the user-interface as a set of static structures and mappings, the UI should be modeled as a set of design preferences. Preferences are frequently many-toone or many-to-many relationships that elude conventional UI modeling, which has lar...

In this article, we propose a method to deal with incomplete interval-valuedhesitant fuzzy preference relations. For this purpose, an additivetransitivity inspired technique for interval-valued hesitant fuzzypreference relations is formulated which assists in estimating missingpreferences. First of all, we introduce a condition for decision makersproviding incomplete information. Decision maker...

Application of Group Decision Support System (GDSS) can assist for delivering the decision of various opinions (preference) cancer detection based on the preferences of various expertise. In this paper we propose ELECTRE-Entropy for GDSS Modeling. We propose entropy weighting for each criteria under ELECTRE Method.ELECTRE is one method in MultiAttribute Decision Making (MADM). Modeling of Group...

Capturing the dynamics in user preference is crucial to better predict future behaviors because preferences often drift over time. Many existing recommendation algorithms -- including both shallow and deep ones model such independently, i.e., static dynamic are not modeled under same latent space, which makes it difficult fuse them for recommendation. This paper considers problem of embedding a...