BACKGROUND Child's gender preference (GP) frequently leads to high fertility which has adverse effect on family health. The link between women's fertility intention, GP and Living Children's Sex Composition (LCSC) as found in this study is less explored in Malawi. OBJECTIVES We examined the relationship between GP, LCSC and fertility intention. METHODS This study utilized 2010 MDHS dataset ...

In previous work [8] we presented a casebased approach to eliciting and reasoning with preferences. A key issue in this approach is the definition of similarity between user preferences. We introduced the probabilistic distance as a measure of similarity on user preferences, and provided an algorithm to compute the distance between two partially specified value functions. This is for the case o...

This introduction gives a brief overview of the field of preference learning and, along the way, tries to establish a unified terminology. Special emphasis will be put on learning to rank, which is by now one of the most extensively studied problem tasks in preference learning and also prominently represented in this book. We propose a categorization of ranking problems into object ranking, ins...

Typically, work on preference elicitation and reasoning about preferences has focused on the problem of specifying, modeling, and optimizing with preference over outcomes corresponding to single objects of interest. In a number of applications, however, the “outcomes” of interest are really sets of such atomic outcomes. For instance, when trying to form coalitions or committees, we need to sele...

PROMETHEEmethods are widely used in Multiple Criteria Decision Aiding (MCDA) to deal with real world decision making problems. In this paper, we propose to apply the Stochastic Multicriteria Acceptability Analysis (SMAA) to the family of PROMETHEEmethods in order to explore the whole set of parameters compatible with some preference information provided by the Decision Maker (DM). The applicati...

Consistency of preference relations is associated with the study of the transitivity property. In this paper, we analyze the properties to be verified by a function, T , in order to obtain the value of preference of the alternative xi over the alternative xk when we already have the values of the preference of xi over xj , and of xj over xk. As a consequence, we define T -additive transitivity ...

Customer preference learning and recommendation for (e-)commerce is a widely researched problem where a number of different solutions have been proposed. In this study we propose and implement a novel approach to the problem of extracting and modelling user preferences in commerce using latent topic models. We explore the use of probabilistic topic models on transaction itemsets considering bot...

Resource allocation is a key problem in autonomic computing. In this paper we use a data center scenario to motivate the need for decentralization and cooperative negotiation, and describe a promising approach that employs preference elicitation. 1 Resource Allocation in an Autonomic

Prior studies using mice have shown that scent marks are an important source of information and can cause behavioural changes in other individuals. Studies have also shown that scent marks in the environment can affect the outcome of social interactions between mice. We used conditioned place preference tests to investigate whether CD-1 male mice (Mus musculus) are reinforced by olfactory cues ...

While decision theory provides an appealing normative framework for representing rich preference structures, eliciting utility or value functions typically incurs a large cost. For many applications involving interactive sys­ tems this overhead precludes the use of for­ mal decision-theoretic models of preference. Instead of performing elicitation in a vacuum, it would be useful if we could aug...