Generic and Update Multi-Document Text Summarization based on Genetic Algorithm

Authors

  • Veronica Neri-Mendoza Universidad Autónoma del Estado de México
  • Yulia Ledeneva Universidad Autónoma del Estado de México
  • Rene Arnulfo García-Hernandez Universidad Autónoma del Estado de México
  • Angel Hernández-Castañeda Universidad Autónoma del Estado de México

DOI:

https://doi.org/10.13053/cys-27-1-4538

Keywords:

Generic, update, multi-document, text summarization, genetic algorithm

Abstract

In this paper, we addressed the generic and update text summarization tasks of a set of documents as a combinatorial optimization problem through a genetic algorithm and unsupervised textual features. Particularly under the news domain, input documents are a set of articles of varying sizes covering the same event. The main advantage of the proposed method is that it is language-independent. The experimental results demonstrated that the method performs well for both kinds of summarization. Moreover, we calculated the heuristics for update text summarization like a benchmark to compare state-of-the-art methods.

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Published

2023-03-30

Issue

Vol. 27 No. 1 (2023): 27(1) 2023

Section

Articles of the Thematic Section

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