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145
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SDM
2007
SIAM
117views Data Mining» more  SDM 2007»
15 years 5 months ago
Discriminating Subsequence Discovery for Sequence Clustering
In this paper, we explore the discriminating subsequencebased clustering problem. First, several effective optimization techniques are proposed to accelerate the sequence mining p...
Jianyong Wang, Yuzhou Zhang, Lizhu Zhou, George Ka...
CVPR
2008
IEEE
16 years 5 months ago
Correlational spectral clustering
We present a new method for spectral clustering with paired data based on kernel canonical correlation analysis, called correlational spectral clustering. Paired data are common i...
Matthew B. Blaschko, Christoph H. Lampert
151
Voted
ICDM
2009
IEEE
176views Data Mining» more  ICDM 2009»
15 years 1 months ago
SISC: A Text Classification Approach Using Semi Supervised Subspace Clustering
Text classification poses some specific challenges. One such challenge is its high dimensionality where each document (data point) contains only a small subset of them. In this pap...
Mohammad Salim Ahmed, Latifur Khan
137
Voted
EDBT
2008
ACM
167views Database» more  EDBT 2008»
16 years 3 months ago
HISSCLU: a hierarchical density-based method for semi-supervised clustering
In situations where class labels are known for a part of the objects, a cluster analysis respecting this information, i.e. semi-supervised clustering, can give insight into the cl...
Christian Böhm, Claudia Plant
IDA
2007
Springer
15 years 9 months ago
DENCLUE 2.0: Fast Clustering Based on Kernel Density Estimation
The Denclue algorithm employs a cluster model based on kernel density estimation. A cluster is defined by a local maximum of the estimated density function. Data points are assign...
Alexander Hinneburg, Hans-Henning Gabriel