Evaluation of text coherence for electronic essay scoring systems
Natural Language Engineering
Information retrieval for language tutoring: an overview of the REAP project
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Changes in scientific articles over two hundred years: a coh-metrix analysis
Proceedings of the 22nd annual international conference on Design of communication: The engineering of quality documentation
Reading level assessment using support vector machines and statistical language models
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Modeling local coherence: An entity-based approach
Computational Linguistics
Revisiting readability: a unified framework for predicting text quality
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Do NLP and machine learning improve traditional readability formulas?
PITR '12 Proceedings of the First Workshop on Predicting and Improving Text Readability for target reader populations
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This paper describes Read-X, a system designed to identify text that is appropriate for the reader given his thematic choices and the reading ability associated with his educational background. To our knowledge, Read-X is the first web-based system that performs real-time searches and returns results classified thematically and by reading level within seconds. To facilitate educators or students searching for reading material at specific reading levels, Read-X extracts the text from the html, pdf, doc, or xml format and makes available a text editor for viewing and editing the extracted text.