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ICDM
2005
IEEE

Online Hierarchical Clustering in a Data Warehouse Environment

9 years 5 months ago
Online Hierarchical Clustering in a Data Warehouse Environment
Many important industrial applications rely on data mining methods to uncover patterns and trends in large data warehouse environments. Since a data warehouse is typically updated periodically in a batch mode, the mined patterns have to be updated as well. This requires not only accuracy from data mining methods but also fast availability of up-to-date knowledge, particularly in the presence of a heavy update load. To cope with this problem, we propose the use of online data mining algorithms which permanently store the discovered knowledge in suitable data structures and enable an efficient adaptation of these structures after insertions and deletions on the raw data. In this paper, we demonstrate how hierarchical clustering methods can be reformulated as online algorithms based on the hierarchical clustering method OPTICS, using a density estimator for data grouping. We also discuss how this algorithmic schema can be specialized for efficient online single-link clustering. A broad e...
Elke Achtert, Christian Böhm, Hans-Peter Krie
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where ICDM
Authors Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger
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