Learning Relevant Models using Symbolic Regression for Automatic Text Summarization
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @Article{DBLP:journals/cys/VazquezLG19,
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author = "Eder {Vazquez Vazquez} and Yulia Ledeneva and
Rene Arnulfo {Garcia Hernandez}",
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title = "Learning Relevant Models using Symbolic Regression for
Automatic Text Summarization",
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journal = "Computacion y Sistemas",
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year = "2019",
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volume = "23",
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number = "1",
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pages = "127",
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keywords = "genetic algorithms, genetic programming, NLP, Natural
language processing, gold standard, topline, symbolic
regression, data modeling, automatic text summarisation
task, ATS",
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ISSN = "1405-5546",
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timestamp = "Thu, 11 Feb 2021 23:28:05 +0100",
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biburl = "https://dblp.org/rec/journals/cys/VazquezLG19.bib",
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bibsource = "dblp computer science bibliography, https://dblp.org",
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URL = "http://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/2921",
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URL = "https://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/2921",
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URL = "https://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/2921/2604",
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DOI = "doi:10.13053/CyS-23-1-2921",
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size = "15 pages",
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abstract = "Natural Language Processing (NLP) methods allow us to
understand and manipulate natural language text or
speech to do useful things. There are several specific
techniques in this area, and although new approaches to
solving the problems arise, its evaluation remains
similar. NLP methods are regularly evaluated by a gold
standard, which contains the correct results which must
be obtained by a method. In this situation, it is
desirable that NLP methods can close as possible to the
results of the gold standard being evaluated. One of
the most outstanding NLP task is the Automatic Text
Summarization (ATS). ATS task consists in reducing the
size of a text while preserving their information
content. In this paper, a method for describing the
ideal behavior (gold standard) of an ATS system, is
proposed. The proposed method can obtain models that
describe the ideal behavior which is described by the
topline. In this work, eight models for ATS are
obtained. These models generate better results than
other models used in the state-of-the-art on ATS
task.",
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notes = "in English",
- }
Genetic Programming entries for
Eder Vazquez Vazquez
Yulia Nikolaevna Ledeneva
Rene Arnulfo Garcia Hernandez
Citations