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Database classification for multi-database mining

delete2005-03-01
delete96
PRE
AI
X
Xindong Wu
张
张承启 (Chengqi Zhang)
S
Shichao Zhang
DOI:10.1016/j.is.2003.10.001delete
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Abstract

Abstract

En 中文
Many large organizations have multiple databases distributed in different branches, and therefore multi-database mining is an important task for data mining. To reduce the search cost in the data from all databases, we need to identify which databases are most likely relevant to a data mining application. This is referred to as database selection. For real-world applications, database selection has to be carried out multiple times to identify relevant databases that meet different applications. In particular, a mining task may be without reference to any specific application. In this paper, we present an efficient approach for classifying multiple databases based on their similarity between each other. Our approach is application-independent. (C) 2003 Elsevier Ltd. All rights reserved.
Keywords:
database selection
classification
multi-database mining
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Journal

Enterprise Information Systems cover
Enterprise Information Systems
IF:
3.9
Papers:
2.8K
Citations:
1.8K

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