VENCE: A new machine learning method enhanced by ontological knowledge to extract summaries

Obtaining extractive summaries by using functions induced from a training set continue to be a great challenge in the domain of the automatic text summary. This paper presents the VENCE method based on this approach and improves the quality of the abduced functions, using semantic relations of the words (attributes) of the training set that are fetched from a ontology to be inserted in this set. The choice of this training set is reinforced with the optimization of the space of attributes by means of statistical techniques, as well as with the introduction of the Jaccard index, calculated from considering a manual summary that is extracted from the corpus of the chosen documents. The VENCE method is explained in details as well as the different experiments conducted to propose an optimal process. Its application to a text document corpus highlighted its efficiency. The results obtained are very satisfactory for the assessment of discriminating power of the abduced classification function as well as for the quality of summaries produced.