Towards Detection of Anomalies in Building Management Data

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Authors

POPELÍNSKÝ Lubomír GLOS Petr

Year of publication 2010
Type Article in Proceedings
Conference 15th IBIMA conference on Knowledge Management and Innovation: A Business Competitive Edge Perspective
MU Faculty or unit

Faculty of Informatics

Citation
Web http://www.ibima.org/CA2010/index.html
Field Informatics
Keywords Building management; data mining; exceptions.
Description This paper aims at finding anomalies in multidimensional spatio-temporal data. We focus on building management data and describe a novel method for mining anomalies in those data. The main idea lies in building a model inductively from data and then in finding examples that are incorrectly classified by this model. Those exceptions are visualized. We describe experiments with three tree learning algorithms for different classification tasks and discuss the results.
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