A Feature Ranking Component for GIS Architecture

Abstract

For a Geographical Information System, it is wanted to design a permanent architectural component which is committed to select relevant information from large databases and network of sensors, and useful in the wide range of applications that such system is destined to. This component allows the system to reach an optimal performance with savings on data acquisition costs and computational resources. The component is based on Data Mining technology and uses feature extraction algorithms to rank the relevance of the dataset features. In all applications reducible to a classification of geographical objects, the feature ranking procedure highlights the features with higher class discriminatory power. Features Ranking is also a cognitive strategy, and produces models of interest toward an artificial intelligent system. The GIS is a Decision Support System (DSS), whereas the feature ranking component supports a within processing decisional activity. A prototype of this component has been assembled and tested on several geographical dataset with promising results at current research stage.

A novel feature ranking modelling in GIS context: Addressing complexity and cost issues

“…The approach we propose in feature ranking, as we have already introduced in [8], has the following characteristics:…”