Readability assessment for text simplification
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Abstract
We describe a readability assessment approach to support the process of text simplification for poor literacy readers. Given an input text, the goal is to predict its readability level, which corresponds to the literacy level that is expected from the target reader: rudimentary, basic or advanced. We complement features traditionally used for readability assessment with a number of new features, and experiment with alternative ways to model this problem using machine learning methods, namely classification, regression and ranking. The best resulting model is embedded in an authoring tool for Text Simplification.
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118
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Authors
1Topics & keywords
Keywords
- Readability
- Computer science
- Ranking (information retrieval)
- Complement (music)
- Natural language processing
- Information retrieval
- Artificial intelligence
- Process (computing)
UN Sustainable Development Goals
- Quality Education
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