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A New Multi-layered Approach for Automatic Text Summaries Mono-Document Based on Social Spiders

Abstract : In this paper, we propose a new multi layer approach for automatic text summarization by extraction where the first layer constitute to use two techniques of extraction: scoring of phrases, and similarity that aims to eliminate redundant phrases without losing the theme of the text. While the second layer aims to optimize the results of the previous layer by the metaheuristic based on social spiders. the objective function of the optimization is to maximize the sum of similarity between phrases of the candidate summary in order to keep the theme of the text, minimize the sum of scores in order to increase the summarization rate, this optimization also will give a candidate’s summary where the order of the phrases changes compared to the original text.The third and final layer aims to choose the best summary from the candidate summaries generated by layer optimization, we opted for the technique of voting with a simple majority.
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Submitted on : Friday, May 11, 2018 - 3:11:07 PM
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Mohamed Amine Boudia, Reda Mohamed Hamou, Abdelmalek Amine, Mohamed Elhadi Rahmani, Amine Rahmani. A New Multi-layered Approach for Automatic Text Summaries Mono-Document Based on Social Spiders. 5th International Conference on Computer Science and Its Applications (CIIA), May 2015, Saida, Algeria. pp.193-204, ⟨10.1007/978-3-319-19578-0_16⟩. ⟨hal-01789959⟩



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