Some issues on complex networks for author characterization

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1. Verfasser: Lucas Antiqueira
Format: Artículo científico
Sprache:en
Veröffentlicht: Asociación Española para la Inteligencia Artificial 2007
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author Lucas Antiqueira
author_facet Lucas Antiqueira
contents Some issues on complex networks for author characterization Lucas Antiqueira Thiago Alexandre Salgueiro Pardo Maria das Graças Volpe Nunes Osvaldo N. Oliveira Jr. Ingeniería Complex Networks Authorship Attribution This paper presents a modeling technique of texts as complex networks and the investigation of the correlationbetween the properties of such networks and author characteristics. In an experiment with several booksfrom eight authors, we show that the networks produced for each author tend to have specific features,which indicates that complex networks can capture author characteristics and, therefore, could be used forthe traditional task of authorship identification 2007 artículo científico 1137-3601 https://www.redalyc.org/articulo.oa?id=92503608 en http://www.redalyc.org/revista.oa?id=925 Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial application/pdf Asociación Española para la Inteligencia Artificial Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial (España) Num.36 Vol.11
format Artículo científico
id redalyc_92503608
institution Redalyc
language en
publishDate 2007
publisher Asociación Española para la Inteligencia Artificial
spellingShingle Some issues on complex networks for author characterization
Lucas Antiqueira
Ingeniería
Complex Networks
Authorship Attribution
Some issues on complex networks for author characterization Lucas Antiqueira Thiago Alexandre Salgueiro Pardo Maria das Graças Volpe Nunes Osvaldo N. Oliveira Jr. Ingeniería Complex Networks Authorship Attribution This paper presents a modeling technique of texts as complex networks and the investigation of the correlationbetween the properties of such networks and author characteristics. In an experiment with several booksfrom eight authors, we show that the networks produced for each author tend to have specific features,which indicates that complex networks can capture author characteristics and, therefore, could be used forthe traditional task of authorship identification 2007 artículo científico 1137-3601 https://www.redalyc.org/articulo.oa?id=92503608 en http://www.redalyc.org/revista.oa?id=925 Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial application/pdf Asociación Española para la Inteligencia Artificial Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial (España) Num.36 Vol.11
title Some issues on complex networks for author characterization
topic Ingeniería
Complex Networks
Authorship Attribution
url https://www.redalyc.org/articulo.oa?id=92503608