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@inproceedings{910096,
author = {Popelínský, Lubomír and Glos, Petr},
address = {Cairo},
booktitle = {15th IBIMA conference on Knowledge Management and Innovation: A Business Competitive Edge Perspective},
keywords = {Building management; data mining; exceptions.},
language = {eng},
location = {Cairo},
isbn = {978-0-9821489-4-5},
pages = {664-669},
publisher = {IBIMA Publishing},
title = {Towards Detection of Anomalies in Building Management Data},
url = {http://www.ibima.org/CA2010/index.html},
year = {2010}
}
TY - JOUR
ID - 910096
AU - Popelínský, Lubomír - Glos, Petr
PY - 2010
TI - Towards Detection of Anomalies in Building Management Data
PB - IBIMA Publishing
CY - Cairo
SN - 9780982148945
KW - Building management
KW - data mining
KW - exceptions.
UR - http://www.ibima.org/CA2010/index.html
N2 - 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.
ER -
POPELÍNSKÝ, Lubomír a Petr GLOS. Towards Detection of Anomalies in Building Management Data. In \textit{15th IBIMA conference on Knowledge Management and Innovation: A Business Competitive Edge Perspective}. Cairo: IBIMA Publishing, 2010, s.~664-669. ISBN~978-0-9821489-4-5.
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