Although extensive research has been conducted in the field of text-readability and user modelling, scholars and researchers have taken into consideration only linguistic complexity in order to classify a text as readable or not. In this paper, the authors move one step forward by considering one more factor, namely intended reader's skills, and by trying to study text readability from a user-specific perspective. Central to our approach is the notion of the user's profile which carries information regarding the linguistic difficulties a user with dyslexia may experience. Based on the user's profile, they develop heuristics for evaluating text's readability for the specific user. The developed heuristics are incorporated in the text classification services of the iLearnRW project, aiming to facilitate the selection of appropriate/suitable reading resources, written in English or Greek, for children with dyslexia1.
['Chris Litsas', 'Maria Mastropavlou', 'Antonios Symvonis']
Profile-Based Text Classification for Children with Dyslexia