—The ontology learning from text cycle consists of the consecutive phases of term, synonym, concept, taxonomy and relation extraction. In this paper, a proposal towards the unsup...
Witold Abramowicz, Maria Vargas-Vera, Marek Wisnie...
We describe the use of a hierarchical topic model for automatically identifying syntactic and lexical patterns that explicitly state ontological relations. We leverage distant sup...
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
This paper presents a new approach to improving relation extraction based on minimally supervised learning. By adding some limited closed-world knowledge for confidence estimation...
Feiyu Xu, Hans Uszkoreit, Sebastian Krause, Hong L...
We develop a formal framework for comparing different versions of ontologies, and apply it to ontologies formulated in terms of DL-Lite, a family of `lightweight' description...
Roman Kontchakov, Frank Wolter, Michael Zakharyasc...