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Proceedings Paper

Using data mining techniques for building fusion models
Author(s): Zhongfei Zhang; John J. Salerno; Maureen A. Regan; Debra A Cutler
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Paper 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.

Paper Details

Date Published: 21 March 2003
PDF: 11 pages
Proc. SPIE 5098, Data Mining and Knowledge Discovery: Theory, Tools, and Technology V, (21 March 2003); doi: 10.1117/12.487024
Show Author Affiliations
Zhongfei Zhang, Binghamton Univ. (United States)
John J. Salerno, Air Force Research Lab. (United States)
Maureen A. Regan, Dolphin Technologies Inc. (United States)
Debra A Cutler, Dolphin Technologies Inc. (United States)

Published in SPIE Proceedings Vol. 5098:
Data Mining and Knowledge Discovery: Theory, Tools, and Technology V
Belur V. Dasarathy, Editor(s)

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