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date: 18 October 2019

Abstract and Keywords

Over the past decades, information has been made available to a broad audience thanks to the availability of texts on the Web. However, understanding the wealth of information contained in texts can pose difficulties for a number of people including those with poor literacy, cognitive or linguistic impairment, or those with limited knowledge of the language of the text. Text simplification was initially conceived as a technology to simplify sentences so that they would be easier to process by natural-language processing components such as parsers. However, nowadays automatic text simplification is conceived as a technology to transform a text into an equivalent which is easier to read and to understand by a target user. Text simplification concerns both the modification of the vocabulary of the text (lexical simplification) and the modification of the structure of the sentences (syntactic simplification). In this chapter, after briefly introducing the topic of text readability, we give an overview of past and recent methods to address these two problems. We also describe simplification applications and full systems also outline language resources and evaluation approaches.

Keywords: lexical simplification, syntactic simplification, readability, machine learning for simplification, text simplification evaluation, rule-based syntactic simplification, lexical resources, simplification lexicon

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