We present an approach to keyhole plan recognition which uses a dynamic belief (Bayesian) network to represent features of the domain that are needed to identify users’ plans and...
David W. Albrecht, Ingrid Zukerman, Ann E. Nichols...
This paper considers a method that combines ideas from Bayesian learning, Bayesian network inference, and classical hypothesis testing to produce a more reliable and robust test o...
We propose a generalized model with configurable discretizer actuators as a solution to the problem of the discretization of massive numerical datasets. Our solution is based on a ...
We consider the task of aggregating beliefs of several experts. We assume that these beliefs are represented as probability distributions. We argue that the evaluation of any aggr...
Background: The aim of this study was to provide a framework for the analysis of visceral obesity and its determinants in women, where complex inter-relationships are observed amo...