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SDM
2007
SIAM
122views Data Mining» more  SDM 2007»
15 years 9 months ago
Incremental Spectral Clustering With Application to Monitoring of Evolving Blog Communities
In recent years, spectral clustering method has gained attentions because of its superior performance compared to other traditional clustering algorithms such as K-means algorithm...
Huazhong Ning, Wei Xu, Yun Chi, Yihong Gong, Thoma...
DMKD
2004
ACM
127views Data Mining» more  DMKD 2004»
16 years 27 days ago
Discovering spatial patterns accurately with effective noise removal
Cluster analysis is a common approach to pattern discovery in spatial databases. While many clustering techniques have been developed, it is still challenging to discover implicit...
Yu Qian, Kang Zhang
ICIP
2001
IEEE
16 years 9 months ago
Image data mining from financial documents based on wavelet features
In this paper, we present a framework for clustering and classifying cheque images according to their payee-line content. The features used in the clustering and classificationpro...
Ossama El Badawy, Mahmoud R. El-Sakka, Khaled Hass...
FLAIRS
2009
15 years 5 months ago
Mining Default Rules from Statistical Data
In this paper, we are interested in the qualitative knowledge that underlies some given probabilistic information. To represent such qualitative structures, we use ordinal conditi...
Gabriele Kern-Isberner, Matthias Thimm, Marc Finth...
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ICML
2001
IEEE
16 years 8 months ago
Constrained K-means Clustering with Background Knowledge
Clustering is traditionally viewed as an unsupervised method for data analysis. However, in some cases information about the problem domain is available in addition to the data in...
Kiri Wagstaff, Claire Cardie, Seth Rogers, Stefan ...