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A New Approach Based on the Detection of Opinion by SentiWordNet for Automatic Text Summaries by Extraction

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  • Mohamed Amine Boudia

    (GeCoDe Laboratory, Dr. Tahar Moulay University of Saida, Saida, Algeria)

  • Reda Mohamed Hamou

    (GeCoDe Laboratory, Dr. Tahar Moulay University of Saida, Saida, Algeria)

  • Abdelmalek Amine

    (GeCoDe Laboratory, Dr. Tahar Moulay University of Saida, Saida, Algeria)

Abstract

In this paper, the authors 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 (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. Finally, the authors found an opinion threshold interval which generate the optimal assessments.

Suggested Citation

  • Mohamed Amine Boudia & Reda Mohamed Hamou & Abdelmalek Amine, 2016. "A New Approach Based on the Detection of Opinion by SentiWordNet for Automatic Text Summaries by Extraction," International Journal of Information Retrieval Research (IJIRR), IGI Global, vol. 6(3), pages 19-36, July.
    • Handle: RePEc:igg:jirr00:v:6:y:2016:i:3:p:19-36
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