DocumentCode :
2650955
Title :
ReadAid: A Robust and Fully-Automated Readability Assessment Tool
Author :
Qumsiyeh, Rani ; Ng, Yiu-Kai
Author_Institution :
Comput. Sci. Dept., Brigham Young Univ., Provo, UT, USA
fYear :
2011
fDate :
7-9 Nov. 2011
Firstpage :
539
Lastpage :
546
Abstract :
Reading is an integral part of educational development, however, it is frustrating for people who struggle to understand (are not motivated to read, respectively) text documents that are beyond (below, respectively) their readability levels. Finding appropriate reading materials, with or without first scanning through their contents, is a challenge, since there are tremendous amount of documents these days and a clear majority of them are not tagged with their readability levels. Even though existing readability assessment tools determine readability levels of text documents, they analyze solely the lexical, syntactic, and/or semantic properties of a document, which are neither fully-automated, generalized, nor well-defined and are mostly based on observations. To advance the current readability analysis technique, we propose a robust, fully-automated readability analyzer, denoted ReadAid, which employs support vector machines to combine features from the US Curriculum and College Board, traditional readability measures, and the author(s) and subject area(s) of a text document d to assess the readability level of d. ReadAid can be applied for (i) filtering documents (retrieved in response to a web query) of a particular readability level, (ii) determining the readability levels of digitalized text documents, such as book chapters, magazine articles, and news stories, or (iii) dynamically analyzing, in real time, the grade level of a text document being created. The novelty of ReadAid lies on using authorship, subject areas, and academic concepts and grammatical constructions extracted from the US Curriculum to determine the readability level of a text document. Experimental results show that ReadAid is highly effective and outperforms existing state-of-the-art readability assessment tools.
Keywords :
Internet; computer aided instruction; educational institutions; query processing; support vector machines; text analysis; ReadAid; US Curriculum and College Board; Web query; academic concepts; authorship; educational development; fully-automated readability assessment tool; grammatical constructions; readability analysis technique; readability level determination; robust readability assessment tool; subject areas; support vector machines; text documents; Educational institutions; Equations; Mathematical model; Support vector machines; Syntactics; Training; Vectors; Assessment; Readability; SVM;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2011 23rd IEEE International Conference on
Conference_Location :
Boca Raton, FL
ISSN :
1082-3409
Print_ISBN :
978-1-4577-2068-0
Electronic_ISBN :
1082-3409
Type :
conf
DOI :
10.1109/ICTAI.2011.87
Filename :
6103377
Link To Document :
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