Abstract. In this paper, we investigate the problem of repairing unsatisfiable concepts in an OWL ontology in detail, keeping in mind the user perspective as much as possible. We f...
Anomaly detection methods can be very useful in identifying unusual or interesting patterns in data. A recently proposed conditional anomaly detection framework extends anomaly de...
In this work we present algorithms for Minimum Energy Consumption Broadcast Subgraph (MECBS) problem. First, we focus on designing distributed algorithms for MECBS. To our knowled...
In this paper we discuss problems of constructing classifiers from imbalanced data. We describe a new approach to selective preprocessing of imbalanced data which combines local ov...
We propose a new, simple model for the automatic induction of selectional preferences, using corpus-based semantic similarity metrics. Focusing on the task of semantic role labeli...