1836 search results - page 128 / 368 » Mining Clustering Dimensions |
111
Voted
KDD
2004
ACM
16 years 2 months ago
2004
ACM
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
115
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SDM
2009
SIAM
15 years 11 months ago
2009
SIAM
Maximum margin clustering (MMC) has recently attracted considerable interests in both the data mining and machine learning communities. It first projects data samples to a kernel...
135
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ICDM
2007
IEEE
15 years 8 months ago
2007
IEEE
Data streams are often locally correlated, with a subset of streams exhibiting coherent patterns over a subset of time points. Subspace clustering can discover clusters of objects...
99
Voted
ICDM
2003
IEEE
15 years 7 months ago
2003
IEEE
We explore in this paper the efficient clustering of item data. Different from those of the traditional data, the features of item data are known to be of high dimensionality and...
118
Voted
ICDM
2002
IEEE
15 years 6 months ago
2002
IEEE
The k-means algorithm with cosine similarity, also known as the spherical k-means algorithm, is a popular method for clustering document collections. However, spherical k-means ca...