A statistical model for scientific readability
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A machine learning approach to reading level assessment
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CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Cognitively motivated features for readability assessment
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
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EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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EANL '08 Proceedings of the Third Workshop on Innovative Use of NLP for Building Educational Applications
Readability assessment for text simplification
IUNLPBEA '10 Proceedings of the NAACL HLT 2010 Fifth Workshop on Innovative Use of NLP for Building Educational Applications
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IUNLPBEA '10 Proceedings of the NAACL HLT 2010 Fifth Workshop on Innovative Use of NLP for Building Educational Applications
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COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
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A comparison of features for automatic readability assessment
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
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ACM Transactions on Intelligent Systems and Technology (TIST)
Proceedings of the Seventh Workshop on Building Educational Applications Using NLP
Making readability indices readable
PITR '12 Proceedings of the First Workshop on Predicting and Improving Text Readability for target reader populations
ERNESTA: a sentence simplification tool for children's stories in italian
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume 2
Text simplification resources for Spanish
Language Resources and Evaluation
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In this paper, we propose a new approach to readability assessment with a specific view to the task of text simplification: the intended audience includes people with low literacy skills and/or with mild cognitive impairment. READ-IT represents the first advanced readability assessment tool for what concerns Italian, which combines traditional raw text features with lexical, morpho-syntactic and syntactic information. In READ-IT readability assessment is carried out with respect to both documents and sentences where the latter represents an important novelty of the proposed approach creating the prerequisites for aligning the readability assessment step with the text simplification process. READ-IT shows a high accuracy in the document classification task and promising results in the sentence classification scenario.