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The fitness function considering two unsupervised text features: sentence position and coverage. We propose the binary coding representation, selection, crossover, and mutation operators. We test the proposed method on the DUC01 and DUC02 data set, four different tasks (summary lengths 200 and 400 words), for each of the collections of documents (in total, 876 documents) are tested. Besides, we analyze the most frequently used methodologies to summarization. Moreover, different heuristics such as topline, baseline, baseline-random, and lead baseline are calculated. In the results, the proposed method achieves to improve the state-of-art results.<\/jats:p>","DOI":"10.3233\/jifs-179900","type":"journal-article","created":{"date-parts":[[2020,6,9]],"date-time":"2020-06-09T12:56:39Z","timestamp":1591707399000},"page":"2397-2408","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":6,"title":["Unsupervised extractive multi-document text summarization using a genetic algorithm"],"prefix":"10.1177","volume":"39","author":[{"given":"Ver\u00f3nica","family":"Neri-Mendoza","sequence":"first","affiliation":[{"name":"Autonomous University of the State of Mexico, Instituto Literario, Toluca, State of Mexico, Mexico"}]},{"given":"Yulia","family":"Ledeneva","sequence":"additional","affiliation":[{"name":"Autonomous University of the State of Mexico, Instituto Literario, Toluca, State of Mexico, Mexico"}]},{"given":"Ren\u00e9 Arnulfo","family":"Garc\u00eda-Hern\u00e1ndez","sequence":"additional","affiliation":[{"name":"Autonomous University of the State of Mexico, Instituto Literario, Toluca, State of Mexico, Mexico"}]}],"member":"179","published-online":{"date-parts":[[2020,6,6]]},"reference":[{"key":"e_1_3_1_2_2","unstructured":"AguilarJ. 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