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» Comparisons Between Data Clustering Algorithms
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WWW
2010
ACM
14 years 4 months ago
The paths more taken: matching DOM trees to search logs for accurate webpage clustering
An unsupervised clustering of the webpages on a website is a primary requirement for most wrapper induction and automated data extraction methods. Since page content can vary dras...
Deepayan Chakrabarti, Rupesh R. Mehta
EDBT
2008
ACM
154views Database» more  EDBT 2008»
14 years 9 months ago
Data utility and privacy protection trade-off in k-anonymisation
K-anonymisation is an approach to protecting privacy contained within a dataset. A good k-anonymisation algorithm should anonymise a dataset in such a way that private information...
Grigorios Loukides, Jianhua Shao
DASFAA
2008
IEEE
190views Database» more  DASFAA 2008»
14 years 3 months ago
Analysis of Time Series Using Compact Model-Based Descriptions
Abstract. Recently, we have proposed a novel method for the compression of time series based on mathematical models that explore dependencies between different time series. This r...
Hans-Peter Kriegel, Peer Kröger, Alexey Pryak...
CCECE
2006
IEEE
14 years 3 months ago
Survey of Biological High Performance Computing: Algorithms, Implementations and Outlook Research
During recent years there has been an explosive growth of biological data coming from genome projects, proteomics, protein structure determination, and the rapid expansion in digi...
Nasreddine Hireche, J. M. Pierre Langlois, Gabriel...
DAWAK
2006
Springer
14 years 23 days ago
Achieving k-Anonymity by Clustering in Attribute Hierarchical Structures
Abstract. Individual privacy will be at risk if a published data set is not properly de-identified. k-anonymity is a major technique to de-identify a data set. A more general view ...
Jiuyong Li, Raymond Chi-Wing Wong, Ada Wai-Chee Fu...