Abstract
Dengue fever is the world’s fastest growing vector-borne disease. Studying such data aims at better understanding the behaviour of this disease to prevent the dengue propagation. For instance, it may be the case that the number of cases of dengue fever in cities depends on many factors, such as climate conditions, density, sanitary conditions. Experts are interested in using geographical information systems in order to visualize knowledge on maps. For this purpose, we propose to build maps based on gradual patterns. Such maps provide a solution for visualizing for instance the cities that follow or not gradual patterns.
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Aryadinata, Y.S., Lin, Y., Barcellos, C., Laurent, A., Libourel, T. (2014). Mining Epidemiological Dengue Fever Data from Brazil: A Gradual Pattern Based Geographical Information System. In: Laurent, A., Strauss, O., Bouchon-Meunier, B., Yager, R.R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2014. Communications in Computer and Information Science, vol 443. Springer, Cham. https://doi.org/10.1007/978-3-319-08855-6_42
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DOI: https://doi.org/10.1007/978-3-319-08855-6_42
Publisher Name: Springer, Cham
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