@article{2402,
  author = {Ali Benafia, Smaine Mazouzi, Ramdane Maamri, Zaidi Sahnoun, Sara Benafia},
  title = {From Linguistic to Conceptual: A Framework Based on a Pipeline for Building Ontologies from Texts},
  journal = {Journal of Data Processing},
  year = {2017},
  volume = {7},
  number = {4},
  doi = {},
  url = {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, ‘argumental structure’…) 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 (‘Le
Monde’ with annual version ‘2013’). 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.},
}