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ICIP
1997
IEEE
16 years 8 months ago
Minimum-Entropy Clustering and its Application to Lossless Image Coding
The Minimum-Entropy Clustering (MEC) algorithm proposed in this paper provides an optimal method for addressing the non-stationarity of a source with respect to entropy coding. Th...
Farshid Golchin, Kuldip K. Paliwal
ICDE
2004
IEEE
117views Database» more  ICDE 2004»
16 years 8 months ago
Probe, Cluster, and Discover: Focused Extraction of QA-Pagelets from the Deep Web
In this paper, we introduce the concept of a QA-Pagelet to refer to the content region in a dynamic page that contains query matches. We present THOR, a scalable and efficient min...
James Caverlee, Ling Liu, David Buttler
KDD
2002
ACM
138views Data Mining» more  KDD 2002»
16 years 7 months ago
Learning to match and cluster large high-dimensional data sets for data integration
Part of the process of data integration is determining which sets of identifiers refer to the same real-world entities. In integrating databases found on the Web or obtained by us...
William W. Cohen, Jacob Richman
ICDM
2008
IEEE
121views Data Mining» more  ICDM 2008»
16 years 1 months ago
Unifying Unknown Nodes in the Internet Graph Using Semisupervised Spectral Clustering
Most research on Internet topology is based on active measurement methods. A major difficulty in using these tools is that one comes across many unresponsive routers. Different m...
Anat Almog, Jacob Goldberger, Yuval Shavitt
ICPR
2008
IEEE
16 years 1 months ago
Kernel Bisecting k-means clustering for SVM training sample reduction
This paper presents a new algorithm named Kernel Bisecting k-means and Sample Removal (KBK-SR) as a sampling preprocessing for SVM training to improve the scalability. The novel c...
Xiao-Zhang Liu, Guo-Can Feng