In this paper we describe a web content adaptation tool for assisting low-literacy readers to access online information. The"Educational FACILITA" tool provides innovative features and the design of more intuitive interaction models. Especially, we propose an interaction model and web application that explore the Natural Language Processing tasks of lexical elaboration and named entity labeling for improving web accessibility.

We present a study on the text simplification operations undertaken collaboratively by Simple English Wikipedia contributors. The aim is to understand whether a complex-simple parallel corpus involving this version of Wikipedia is appropriate as data source to induce simplification rules, and whether we can automatically categorise the different operations performed by humans. A subset of the corpus was first manually analysed to identify its transformation operations. We then built machine learning models to attempt to automatically classify segments based on such transformations. This classification could be used, e.g., to filter out potentially noisy transformations. Our results show that the most common transformation operations performed by humans are paraphrasing (39.80%) and drop of information (26.76%), which are some of the most difficult operations to generalise from data. They are also the most difficult operations to identify automatically, with the lowest overall classifier accuracy among all operations (73% and 59%, respectively).

This research addresses the topic of Textual Elaboration for low-literacy readers, i.e. people at the rudimentary and basic literacy levels according to the National Indicator of Functional Literacy (INAF, 2009). Text Elaboration consists of a set of techniques that adds extra material in texts using, traditionally, definitions, synonyms, antonyms, or any external information to assist in text understanding. The main goal of this research was the proposal of two methods of Textual Elaboration: (1) the use of short definitions for Named Entities in texts and (2) assignment of wh-questions related to verbs in text. The first task used the Rembrandt named entity recognition system and short definitions of Wikipedia. It was implemented in PorSimples web Educational Facilita tool. This method was preliminarily evaluated with a small group of low-literacy readers. The evaluation results were positive, what indicates that the tool was useful for improving the text understanding. The assignment of wh-questions related to verbs task was defined, studied, implemented and assessed during this research. Its evaluation was conducted with NLP researches instead of with low-literacy readers. There are good evidences that the text elaboration methods and resources developed here are useful in helping text understanding for low-literacy readers.

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