A semi-automatic approach for building ontologies from a collection of structured web documents

Mouna Kamel (1) , Nathalie Aussenac-Gilles (1, 2) , Davide Buscaldi (3) , Catherine Comparot (1, 4)

1 IRIT-MELODI - MEthodes et ingénierie des Langues, des Ontologies et du DIscours
2 CNRS - Centre National de la Recherche Scientifique
3 LIPN - Laboratoire d'Informatique de Paris-Nord
4 UT2J - Université Toulouse - Jean Jaurès

Many collections of structured documents are available on the web. The collection generally describes the characteristics of entities from a single type, where each page describes one entity. These documents are adequate knowledge sources for building ontologies. As they benefit from a strong and shared layout, they contain less well written text than plain text files but their architecture is very meaningful. Classical linguistic-based methods for identifying concepts and relations are no longer appropriate for analyzing them. The approach we propose in this paper exploits various properties of such documents, combining layout/formatting analysis and linguistic analysis, and using semantic annotation.

Mots clés: Document layout; Document structure; Ontology enrichment; Ontology building

Domaines: Intelligence artificielle [cs.AI]; Apprentissage [cs.LG]; Logique en informatique [cs.LO]; Informatique et langage [cs.CL]

Mouna Kamel, Nathalie Aussenac-Gilles, Davide Buscaldi, Catherine Comparot. A semi-automatic approach for building ontologies from a collection of structured web documents. 7th International Conference on Knowledge Capture (K-CAP 2013), Jun 2013, Banff, Canada. pp.139-140, ⟨10.1145/2479832.2479856⟩. ⟨hal-01264565⟩