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Automatic Text Summarization with Genetic Algorithm-Based Attribute Selection

Silla Jr, Carlos N. and Pappa, Gisele L. and Freitas, Alex A. and Kaestner, Celso A.A. (2004) Automatic Text Summarization with Genetic Algorithm-Based Attribute Selection. In: Lemaitre, Christian and Reyes, Carlos A. and Gonzalez, Jesus A., eds. Advances in Artificial Intelligence – IBERAMIA 2004 9th Ibero-American Conference on AI. Lecture Notes in Computer Science . Springer, Berlin, Germany, pp. 305-314. ISBN 978-3-540-23806-5. E-ISBN 978-3-540-30498-2. (doi:10.1007/978-3-540-30498-2_31) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:14060)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1007/978-3-540-30498-2_31

Abstract

The task of automatic text summarization consists of generating a summary of the original text that allows the user to obtain the main pieces of information available in that text, but with a much shorter reading time. This is an increasingly important task in the current era of information overload. given the huge amount of text available in documents. In this paper the automatic text summarization is cast as a classification (supervised learning) problem, so that machine learning-oriented classification methods are used to produce summaries for documents based on a set of attributes describing those documents. The goal of the paper is to investigate the effectiveness of Genetic Algorithm (GA)-based attribute selection in improving the performance of classification algorithms solving the automatic text summarization task. Computational results are reported for experiments with a document base formed by news extracted from The Wall Street Journal of the TIPSTER collection-a collection that is often used as a benchmark in the text summarization literature.

Item Type: Book section
DOI/Identification number: 10.1007/978-3-540-30498-2_31
Uncontrolled keywords: text summarization, attribute selection, multi-objective genetic algorithms
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Mark Wheadon
Date Deposited: 24 Nov 2008 18:01 UTC
Last Modified: 16 Feb 2021 12:24 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/14060 (The current URI for this page, for reference purposes)
Freitas, Alex A.: https://orcid.org/0000-0001-9825-4700
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