Pruning Terminology Extracted from a Specialized Corpus for CV Ontology Acquisition
Abstract
This paper presents an experimental study for extracting a terminology from a corpus made of Curriculum Vitae (CV). This terminology is to be used for ontology acquisition. The choice of the pruning rate of the terminology is crucial relative to the quality of the ontology acquired. In this paper, we investigate this pruning rate by using several evaluation measures (precision, recall, F-measure, and ROC curve).