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ICIP
1997
IEEE
16 years 9 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
299
Voted
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
189
Voted
KDD
2002
ACM
138views Data Mining» more  KDD 2002»
16 years 8 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
204
Voted
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
189
Voted
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