Adapting Web content for low-literacy readers by using lexical elaboration and named entities labeling

  • Authors:

  • W. M. Watanabe;A. Candido, Jr.;M. A. Amancio;M. De Oliveira;T. A. S. Pardo;R. P. M. Fortes;S. M. Aluisio

  • Affiliations:

  • Computer Sciences Department, Institute of Mathematics and Computer Sciences, University of Sao Paulo, Sao Carlos, Brazil;Computer Sciences Department, Institute of Mathematics and Computer Sciences, University of Sao Paulo, Sao Carlos, Brazil;Computer Sciences Department, Institute of Mathematics and Computer Sciences, University of Sao Paulo, Sao Carlos, Brazil;Computer Sciences Department, Institute of Mathematics and Computer Sciences, University of Sao Paulo, Sao Carlos, Brazil;Computer Sciences Department, Institute of Mathematics and Computer Sciences, University of Sao Paulo, Sao Carlos, Brazil;Computer Sciences Department, Institute of Mathematics and Computer Sciences, University of Sao Paulo, Sao Carlos, Brazil;Computer Sciences Department, Institute of Mathematics and Computer Sciences, University of Sao Paulo, Sao Carlos, Brazil

  • Venue:
  • The New Review of Hypermedia and Multimedia - Web Accessibility
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper presents an approach for assisting low-literacy readers in accessing Web online information. The “Educational FACILITA” tool is a Web content adaptation tool that provides innovative features and follows more intuitive interaction models regarding accessibility concerns. Especially, we propose an interaction model and a Web application that explore the natural language processing tasks of lexical elaboration and named entity labeling for improving Web accessibility. We report on the results obtained from a pilot study on usability analysis carried out with low-literacy users. The preliminary results show that “Educational FACILITA” improves the comprehension of text elements, although the assistance mechanisms might also confuse users when word sense ambiguity is introduced, by gathering, for a complex word, a list of synonyms with multiple meanings. This fact evokes a future solution in which the correct sense for a complex word in a sentence is identified, solving this pervasive characteristic of natural languages. The pilot study also identified that experienced computer users find the tool to be more useful than novice computer users do.