Eunice Kennedy Shriver Center; Department of Family Medicine and Community Health
Artificial Intelligence and Robotics | Cognitive Neuroscience | Disability Studies | Graphics and Human Computer Interfaces | Information Literacy
Text simplification (TS) aims to reduce the lexical and structural complexity of a text, while still retaining the semantic meaning. Current automatic TS techniques are limited to either lexical-level applications or manually defining a large amount of rules. In this paper, we propose to simplify text from both level of lexicons and sentences. We conduct preliminary experiments to find that our approach shows promising results.
Automatic Text Simplification, Natural Language Processing
Rights and Permissions
Copyright 2017 World Scientific Publishing Company. Author accepted manuscript posted as allowed by the publisher's author rights policy at https://www.worldscientific.com/page/authors/author-rights.
DOI of Published Version
Chen, P., Rochford, J., Kennedy, D. N., Djamasbi, S., Fay, P., & Scott, W. (2017). Automatic Text Simplification for People with Intellectual Disabilities. In 2016 International Conference on Artificial Intelligence Science and Technology (AIST2016) (pp. 725–731). DOI: 10.1142/9789813206823_0091. Link to publisher website
2016 International Conference on Artificial Intelligence Science and Technology (AIST2016)
Chen P, Rochford J, Kennedy DN, Djamasbi S, Fay P, Scott W. (2017). Automatic Text Simplification for People with Intellectual Disabilities. Eunice Kennedy Shriver Center Publications. https://doi.org/10.1142/9789813206823_0091. Retrieved from https://escholarship.umassmed.edu/shriver_pp/68