From Linguistic to Conceptual: A Framework Based on a Pipeline for Building Ontologies from Texts
Ali Benafia, Smaine Mazouzi, Ramdane Maamri, Zaidi Sahnoun, Sara Benafia
Journal of Data Processing, Vol. 7, No. 4, 2017.
DOI: 
Link: http://www.dline.info/jdp/fulltext/v7n4/jdpv7n4_3.pdf
Abstract:
This paper presents a novel approach of information extraction for building ontologies covering an extensive
range of applications from corpora. Our goal is to propose a method that is independent of domains and based on a distributional
analysis of semantic units to bring out all the candidates informative elements (concepts, entities, semantic relations,
named entities ...).This method is based on a pipeline of four main stages allowing to refine the extraction information from
unstructured text in the form of a suite of decomposable representations (sentences in triplets, â€˜argumental structureâ€™â€¦) until
to get a consistent final ontology.
We applied the pipeline defined in the context of a repeated sampling of 100 articles randomly drawn from text corpus (â€˜Le
Mondeâ€™ with annual version â€˜2013â€™). For the evaluation results of the trial implementation of our system , we have achieved a
level of accuracy at which was up to 74% . We believe from the results obtained that our methodology is quite generic, and can
be easily adapted to any new domain.