2005 Text2Onto

• (Cimiano & Völker, 2005) ⇒ Philipp Cimiano, Johanna Völker. (2005). “Text2Onto - A Framework for Ontology Learning and Data-driven Change Discovery.” In: Proceedings of the 10th International Conference on Applications of Natural Language to Information Systems (NLDB-2005).

Subject Headings: Ontology Learning, Relation Detection from Text Algorithm, Text2Onto

Cited By

~11 http://scholar.google.com/scholar?cites=16893030024429433993

Quotes

Abstract

• In this paper we present Text2Onto, a framework for ontology learning from textual resources. Three main features distinguish Text2Onto from our earlier framework TextToOnto as well as other state-of-the-art ontology learning frameworks. First, by representing the learned knowledge at a meta-level in the form of instantiated modeling primitives within a so called Probabilistic Ontology Model (POM), we remain independent of a concrete target language while being able to translate the instantiated primitives into any (reasonably expressive) knowledge representation formalism. Second, user interaction is a core aspect of Text2Onto and the fact that the system calculates a confidence for each learned object allows to design sophisticated visualizations of the POM. Third, by incorporating strategies for data-driven change discovery, we avoid processing the whole corpus from scratch each time it changes, only selectively updating the POM according to the corpus changes instead. Besides increasing efficiency in this way, it also allows a user to trace the evolution of the ontology with respect to the changes in the underlying corpus.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2005 Text2Onto	Philipp Cimiano Johanna Völker			Text2Onto - A Framework for Ontology Learning and Data-driven Change Discovery		Proceedings of the 10th International Conference on Applications of Natural Language to Information System	http://www.aifb.uni-karlsruhe.de/WBS/jvo/publications/Text2Onto nldb 2005.pdf			2005