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What is Collaborators

Chapter 19
Handbook of Research on 3-D Virtual Environments and Hypermedia for Ubiquitous Learning
People who have similar characteristics in terms of both profiles as the choices made about content.
Published in Chapter:
Content Personalized Recommendation Engine to Support an Informal Learning Environment in the Health Context
Alisson Alan Lima da Costa (Rural Federal University of Semi-Arid, Brazil), Francisco Milton Mendes Neto (Rural Federal University of Semi-Arid, Brazil), Enio Lopes Sombra (Rural Federal University of Semi-Arid, Brazil), Jonathan Darlan Cunegundes Moreira (Rural Federal University of Semi-Arid, Brazil), Rafael Castro de Souza (Rural Federal University of Semi-Arid, Brazil), and Jerffeson Gomes Dutra (Rural Federal University of Semi-Arid, Brazil)
Copyright: © 2016 |Pages: 32
DOI: 10.4018/978-1-5225-0125-1.ch019
Abstract
People with chronic diseases suffer with limitations imposed by their health condition and learn more about the disease helps in improving the quality of life. This is possible because the use in mass of mobile devices and the advent of Web 2.0 tools, which gave rise to the Health 2.0 concept. This search for the construction of knowledge by stimulating citizens to be active and responsible for their health. However, provide contextualized knowledge at the right time, it is not a trivial task due to the diversity of content and user's profiles. The solution to this is to provide informal learning through personalized recommendation of content by providing relevant content to users related to their health. This chapter proposes a personalized recommendation system of content, which includes the union of different recommendation techniques and genetic algorithm, seeking efficacy on the recommendation of the contents to people with chronic diseases aiming informal learning in health.
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