The recent years have witnessed a surge of interests in semi-supervised learning methods. A common strategy for these algorithms is to require that the predicted data labels shoul...
In this paper we describe an intuitionistic method for dependency parsing, where a classifier is used to determine whether a pair of words forms a dependency edge. And we also pro...
In this paper, the problem of discovering anomalies in a large-scale network based on the data fusion of heterogeneous monitors is considered. We present a classification of anoma...
In this paper, we report our success in building efficient scalable classifiers in the form of decision tables by exploring capabilities of modern relational database management s...
In many application domains, classification tasks have to tackle multiclass imbalanced training sets. We have been looking for a CBA approach (Classification Based on Association r...