Publications du laboratoire
|A New Framework for Taxonomy Discovery from Text |
Auteur(s): ELSAYED A., HACID H., ZIGHED D. A.
Actes de conférence: Conference: Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 08), Osaka, Japan (Osaka, JP, 2008-05-20) Publié: Advances in Knowledge Discovery and Data Mining, vol. 5012/2008 (2008) p.985-991
Résumé: Ontology learning from text is considered as an appealing and a challenging approach to address the shortcomings of the hand-crafted ontologies. In this paper, we present OLEA, a new framework for ontology learning from text. The proposal is a hybrid approach combining the pattern-based and the distributional approaches. It addresses key issues in the area of ontology learning: low recall of the pattern-based approach, low precision of the distributional approach, and finally ontology evolution. Preliminary experiments performed at each stage of the learning process show the pros and cons of the proposal.