Paper Title
Spatial Data Management System for Dengue and Swineflu Epidemiology

Abstract
Recent developments in information technology have enabled collection and processing of vast amounts of personal data, business data and spatial data. It has been widely recognized that spatial data analysis capabilities have not kept up with the need for analyzing the increasingly large volumes of geographic data of various themes that are currently being collected and archived. Our study is carried out on the way to provide the mission-goal strategy (requirements) to predict the epidemic. The co-location rules of spatial data mining are proved to be appropriate to design nuggets for disaster identification and the state-of-the-art and emerging scientific applications require fast access of large quantities of data. Large databases are routinely being collected in science, business and medicine. It has been widely recognized that spatial data analysis capabilities have not kept up with the need for analyzing the increasingly large volumes of geographic data of various themes that are currently being collected and archived. This management system is to obtain and process the data, to interpret the data, and to use the designed algorithms for decision makers (Health Companion) as a basis for action. Our contribution in this paper is to design Algorithms to identify spreading of the dengue from huge datasets Keywords - Spatial Data Mining; Data Sets; Algorithms; Dengue; Knowledge; Collocation Pattern.

Author - V. Shankar

Published : Volume-5,Issue-9  ( Sep, 2018 )

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