Using data mining techniques for building fusion models

Zhongfei Zhang; John J. Salerno; Maureen A. Regan; Debra A Cutler

doi:10.1117/12.487024

21 March 2003 Using data mining techniques for building fusion models

Zhongfei Zhang, John J. Salerno, Maureen A. Regan, Debra A Cutler

Proceedings Volume 5098, Data Mining and Knowledge Discovery: Theory, Tools, and Technology V; (2003) https://doi.org/10.1117/12.487024
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

Over the past decade many techniques have been developed which attempt to predict possible events through the use of given models or patterns of activity. These techniques work quite well given the case that one has a model or a valid representation of activity. However, in reality for the majority of the time this is not the case. Models that do exist, in many cases were hand crafted, required many man-hours to develop and they are very brittle in the dynamic world in which we live. Data mining techniques have shown some promise in providing a set of solutions. In this paper we will provide the details for our motivation, theory and techniques which we have developed, as well as the results of a set of experiments.

Citation Download Citation

Zhongfei Zhang, John J. Salerno, Maureen A. Regan, and Debra A Cutler "Using data mining techniques for building fusion models", Proc. SPIE 5098, Data Mining and Knowledge Discovery: Theory, Tools, and Technology V, (21 March 2003); https://doi.org/10.1117/12.487024

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