Reda Mohamed HAMOU, Mohamed Amine BOUDIA and Abdelmalek AMINE, Dr. Moulay Tahar University Saida, Algeria

In this paper, we propose a new approach based on the detection of opinion by the SentiWordNet for the production of text summarization by using the scoring extraction technique adapted to detecting of opinion. The texts are decomposed into sentences then represented by a vector of scores of opinion of this sentences. The summary will be done by elimination of sentences whose opinion is different from the original text. This difference is expressed by a threshold opinion. The following hypothesis: "textual units that do not share the same opinion of the text are ideas used for the development or comparison and their absences have no vocation to reach the semantics of the abstract" Has been verified by the statistical measure of Chi_2 which we used it to calculate a dependence between the unit textual and the text. Finally we found an opinion threshold interval which generate the optimal assessments.

Automatic Summary Extraction, Text Mining, Evaluation, Automatic Language Processing, F-Measure, correlation, ROUGE-SU (2), SentiWordNet, Opinion Mining.