Sciweavers

Share
SADM
2008

Global Correlation Clustering Based on the Hough Transform

8 years 8 months ago
Global Correlation Clustering Based on the Hough Transform
: In this article, we propose an efficient and effective method for finding arbitrarily oriented subspace clusters by mapping the data space to a parameter space defining the set of possible arbitrarily oriented subspaces. The objective of a clustering algorithm based on this principle is to find those among all the possible subspaces that accommodate many database objects. In contrast to existing approaches, our method can find subspace clusters of different dimensionality even if they are sparse or are intersected by other clusters within a noisy environment. A broad experimental evaluation demonstrates the robustness and effectiveness of our method. 2008 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 1: 111
Elke Achtert, Christian Böhm, Jörn David
Added 28 Dec 2010
Updated 28 Dec 2010
Type Journal
Year 2008
Where SADM
Authors Elke Achtert, Christian Böhm, Jörn David, Peer Kröger, Arthur Zimek
Comments (0)
books