A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Deriving concept hierarchies from text
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
IEEE Internet Computing
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Learning concept hierarchies from text corpora using formal concept analysis
Journal of Artificial Intelligence Research
Graph connectivity measures for unsupervised word sense disambiguation
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
On how to perform a gold standard based evaluation of ontology learning
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
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In this paper, we propose the Automatic Taxonomy Construction from Text (ATCT) framework for building taxonomies from text-based Web corpora. The framework is composed of multiple processing steps. Firstly, domain terms are extracted using a filtering method. Subsequently, Word Sense Disambiguation (WSD) is optionally applied in order to determine the senses of these terms. Then, by means of a subsumption technique, the resulting concepts are arranged in a hierarchy. We construct taxonomies with and without WSD and we investigate the effect of WSD on the quality of concept type-of relations using an evaluation framework that uses a golden taxonomy. We find that WSD improves the quality of the built taxonomy in terms of the taxonomic F-Measure.