Conventional methods used for the interpretation of activation data provided by functional neuroimaging techniques provide useful insights on what the networks of cerebral structu...
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
We present a computational framework to automatically discover high-order temporal social patterns from very noisy and sparse location data. We introduce the concept of social foo...
Students’ actions while working with a tuoring system were used to generate estimates of learning goals, specifically, the goal of learning by using multimedia help resources, an...
BAYDA is a software package for flexible data analysis in predictive data mining tasks. The mathematical model underlying the program is based on a simple Bayesian network, the Na...