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A New Memetic Algorithm for Multi-document Summarization Based on CHC Algorithm and Greedy Search

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Human-Inspired Computing and Its Applications (MICAI 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8856))

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Abstract

Multi-document summarization has been used for extracting the most relevant sentences from a set of documents, allowing the user to more quickly address the content thereof. This paper addresses the generation of extractive summaries from multiple documents as a binary optimization problem and proposes a method, based on CHC evolutionary algorithm and greedy search, called MA-MultiSumm, in which objective function optimizes the lineal combination of coverage and redundancy factors. MA-MultiSumm was compared with other state-of-the-art methods using ROUGE measures. The results showed that MA-MultiSumm outperforms all methods on the DUC2005 dataset; and on DUC2006 the results are very close to the best method. Furthermore in a unified ranking MA-MultiSumm only was improved on by the DESAMC+DocSum method, which requires as many iterations of the evolutionary process as MA-MultiSumm. The experimental results show that the optimization-based approach for multiple document summarization is truly a promising research direction.

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Author information

Authors and Affiliations

  1. Universidad del Cauca, Popayán, Colombia

    Martha Mendoza & Carlos Cobos

  2. Universidad Nacional de Colombia, Bogotá D.C., Colombia

    Elizabeth León

  3. Universidad de Granada, Granada, España

    Manuel Lozano, Francisco Rodríguez & Enrique Herrera-Viedma

Authors
  1. Martha Mendoza
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  2. Carlos Cobos
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  3. Elizabeth León
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  4. Manuel Lozano
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  5. Francisco Rodríguez
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  6. Enrique Herrera-Viedma
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Editor information

Editors and Affiliations

  1. Centro de Investigación en Computación, Instituto Politécnico Nacional, Av. Juan Dios Bátiz s/n, Col. Nueva Industrial Vallejo, 07738, Mexico City, Mexico

    Alexander Gelbukh

  2. Área Académica de Computación y Electrónica, Carretera Pachuca-Tulancingo, Universidad Autónoma del Estado de Hidalgo, Km. 4.5, Col. Carboneras, Mineral de la Reforma, 42180, Hidalgo, Mexico

    Félix Castro Espinoza

  3. Facultad de ciencias, Universidad Autónoma Nacional de México, Ciudad Universitaria, México DF, Mexico

    Sofía N. Galicia-Haro

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Mendoza, M., Cobos, C., León, E., Lozano, M., Rodríguez, F., Herrera-Viedma, E. (2014). A New Memetic Algorithm for Multi-document Summarization Based on CHC Algorithm and Greedy Search. In: Gelbukh, A., Espinoza, F.C., Galicia-Haro, S.N. (eds) Human-Inspired Computing and Its Applications. MICAI 2014. Lecture Notes in Computer Science(), vol 8856. Springer, Cham. https://doi.org/10.1007/978-3-319-13647-9_14

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  • DOI: https://doi.org/10.1007/978-3-319-13647-9_14

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13646-2

  • Online ISBN: 978-3-319-13647-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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