Single Extractive Text Summarization Based on a Genetic Algorithm

  • René Arnulfo García-Hernández
  • Yulia Ledeneva
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7914)


Extractive text summarization consists in selecting the most important units (normally sentences) from the original text, but it must be done as closer as humans do. Several interesting automatic approaches are proposed for this task, but some of them are focused on getting a better result rather than giving some assumptions about what humans use when producing a summary. In this research, not only the competitive results are obtained but also some assumptions are given about what humans tried to represent in a summary. To reach this objective a genetic algorithm is proposed with special emphasis on the fitness function which permits to contribute with some conclusions.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • René Arnulfo García-Hernández
    • 1
  • Yulia Ledeneva
    • 1
  1. 1.Autonomous University of the State of MexicoSantiago TianguistencoMéxico

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