6533b82afe1ef96bd128c104
RESEARCH PRODUCT
An approach for recommending personalized contents for homecare users in the context of health 2.0
Jonathan Darlan Cunegundes MoreiraRicardo Alexsandro De Medeiros ValentimAlisson Alan Lima Da CostaEnio Lopes SombraCecilia Dias FloresJ. Javier SamperFrancisco Milton Mendes NetoRogério Patrício Chagas Do Nascimentosubject
User profileMultimediaComputer sciencebusiness.industryContext (language use)Ontology (information science)computer.software_genreWorld Wide WebHealth careUser interfacebusinessMobile devicecomputerUbiquitous learningdescription
This paper proposes a content recommendation mechanism as part of a model for implementing ubiquitous learning for supporting people with chronic diseases who are treated at home, so that they can learn more about treatments for their disease. In the proposed approach, the learning takes place based on day-to-day activities and real situations. In this case, the model supports the development of tools that can learn about the user's context, based on data obtained via sensors installed on users or in their home, as well as data supplied directly by the user interface of their mobile devices, and data provided by the healthcare team, and, after that, recommend contents about their diseases.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2014-04-02 | Proceedings of the 7th Euro American Conference on Telematics and Information Systems |