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» Clustering Multi-represented Objects with Noise
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PAKDD
2004
ACM
94views Data Mining» more  PAKDD 2004»
13 years 10 months ago
Clustering Multi-represented Objects with Noise
Abstract. Traditional clustering algorithms are based on one representation space, usually a vector space. However, in a variety of modern applications, multiple representations ex...
Karin Kailing, Hans-Peter Kriegel, Alexey Pryakhin...
ICDE
2008
IEEE
124views Database» more  ICDE 2008»
14 years 6 months ago
Mining Approximate Order Preserving Clusters in the Presence of Noise
Subspace clustering has attracted great attention due to its capability of finding salient patterns in high dimensional data. Order preserving subspace clusters have been proven to...
Mengsheng Zhang, Wei Wang 0010, Jinze Liu
IJIT
2004
13 years 6 months ago
On the Noise Distance in Robust Fuzzy C-Means
In the last decades, a number of robust fuzzy clustering algorithms have been proposed to partition data sets affected by noise and outliers. Robust fuzzy C-means (robust-FCM) is c...
Mario G. C. A. Cimino, Graziano Frosini, Beatrice ...
SIGMOD
2004
ACM
154views Database» more  SIGMOD 2004»
14 years 4 months ago
Computing Clusters of Correlation Connected Objects
The detection of correlations between different features in a set of feature vectors is a very important data mining task because correlation indicates a dependency between the fe...
Christian Böhm, Karin Kailing, Peer Krög...
ICMCS
2007
IEEE
124views Multimedia» more  ICMCS 2007»
13 years 11 months ago
Robust Video Object Segmentation Based on K-Means Background Clustering and Watershed in Ill-Conditioned Surveillance Systems
A robust video object segmentation algorithm for complex conditions in surveillance systems is proposed in this paper. This algorithm contains an unsupervised K-Means background c...
Tse-Wei Chen, Shou-Chieh Hsu, Shao-Yi Chien