Data Mining for Hierarchical Model Creation
Youngblood, G.M.; Cook, D.J.
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
Volume 37, Issue 4, July 2007 Page(s):561 - 572
Digital Object Identifier   10.1109/TSMCC.2007.897341
Summary:In this paper, we examine the problem of learning inhabitant behavioral models in intelligent environments. We maintain that inhabitant interactions in smart environments can be automated using a data-driven approach to generate hierarchical inhabitant models and learn decision policies. To validate this hypothesis, we have designed the ProPHeT decision-learning algorithm that learns a strategy for controlling a smart environment based on sensor observation, power line control, and the generated hierarchical model. The performance of the algorithm is evaluated using real data collected from our MavHome smart home and smart office environments.

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