This paper studies a possibility to learn a complex user preference model, based on CP-nets, from user ratings. This work is motivated by the need of user modelling in decision making support, for example in e-commerce. We extend our user model based on fuzzy logic to capture variation of preference objectives. The proposed method 2CP-regression is described and tested. 2CPregression uses CP-ne...

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...

Topological separability is crucial for the utility representation of a complete preference relation. When preferences are incomplete, this axiom has suitably de…ned counterparts: upper separability and lower separability (Ok (2002)). We consider the problem of representing an incomplete preference relation by means of a vector-valued utility function; we obtain representation results under the...

Multi criteria decision making (MCDM) methods like analytic hierarchy process, ELECTRE and multi-attribute utility theory are critically studied. They have irregularities in terms of the reliability of ranking of the best alternatives. The Routing Decision Support (RDS) algorithm is trying to improve some of their deficiencies. This paper gives a mathematical verification that the RDS algorithm...

In this paper we describe our effort on 2016 Contextual Suggestion Track. We present a new ranking model that captures both global trend of interests as well as contextual individual preference. We trained a regressor on common users data thus it can prioritize popular places and categories. In order to model individual user preference, we introduce word embeddings to represent both user profil...