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Computación y Sistemas

Print version ISSN 1405-5546

Comp. y Sist. vol.17 n.2 México Apr./Jun. 2013

 

Artículos

 

Automatic Readability Classification of Crowd-Sourced Data based on Linguistic and Information-Theoretic Features

 

Clasificación automática de la legibilidad de datos de fuentes múltiples basada en características lingüísticas y de la teoría de información

 

Zahurul Islam1 and Alexander Mehler2

 

1 AG Texttechnology, Instituí fur Informatik, Goethe-Universitat, Frankfurt, Germany mehler@em.uni-frankfurt.de

2 AG Texttechnology, Instituí fur Informatik, Goethe-Universitat, Frankfurt, Germany

 

Article received on 12/12/2012
Accepted on 16/02/2013.

 

Abstract

This paper presents a classifier of text readability based on information-theoretic features. The classifier was developed based on a linguistic approach to readability that explores lexical, syntactic and semantic features. For this evaluation we extracted a corpus of 645 articles from Wikipedia together with their quality judgments. We show that information-theoretic features perform as well as their linguistic counterparts even if we explore several linguistic levels at once.

Keywords: Text readability, Wikipedia, enthropy, information transmission, evaluation of features.

 

Resumen

En este trabajo se presenta un clasificador de la legibilidad de textos basado en las características de la teoría de información. El clasificador ha sido desarrollado en base del enfoque lingüístico a la legibilidad usando las características léxicas, sintácticas y semánticas. Para esta evaluación se extrajo un corpus de 645 artículos de Wikipedia, junto con sus evaluaciones de calidad. Se demuestra que las características mencionadas tienen buen desempeño, incluso en el caso cuando se exploran varios niveles lingüísticos a la vez.

Palabras clave: Legibilidad de textos, Wikipedia, entropía, transmisión de información, evaluación de características.

 

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