Une mesure de proximité et une méthode de regroupement pour l'aide à l'acquisition d'ontologies spécialisées

Abstract : In this paper, we study the problem of clustering textual units in the framework of helping an expert to build a specialized ontology. This work has been achieved in the context of a French project, called BIOTIM, handling botany corpora. %One of its goal is the acquisition of a semantic organization from textual information. Building an ontology, either automatically or semi-automatically is a difficult task. We focus on one of the main steps of that process, namely structuring the textual units occurring in the texts into classes, likely to represent concepts of the domain. The approach that we propose relies on the definition of a new non-symmetrical measure for evaluating the semantic proximity between lemma, taking into account the contexts in which they occur in the documents. Moreover, we present a non-supervised classification algorithm designed for the task at hand and that kind of data. The first experiments performed on botanical data have given relevant results.
Document type :
Conference papers
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-00084787
Contributor : Guillaume Cleuziou <>
Submitted on : Monday, July 10, 2006 - 3:46:09 PM
Last modification on : Thursday, January 17, 2019 - 3:06:06 PM

Identifiers

  • HAL Id : hal-00084787, version 1

Collections

Citation

Guillaume Cleuziou, Sylvie Billot, Stanislas Lew, Lionel Martin, Christel Vrain. Une mesure de proximité et une méthode de regroupement pour l'aide à l'acquisition d'ontologies spécialisées. Extraction et Gestion des Connaissances (EGC'2006), 2006, France. pp.163-174. ⟨hal-00084787⟩

Share

Metrics

Record views

114