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» A clustering method that uses lossy aggregation of data
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ECML
2006
Springer
14 years 24 days ago
Subspace Metric Ensembles for Semi-supervised Clustering of High Dimensional Data
A critical problem in clustering research is the definition of a proper metric to measure distances between points. Semi-supervised clustering uses the information provided by the ...
Bojun Yan, Carlotta Domeniconi
IEEEARES
2008
IEEE
14 years 3 months ago
A Post-processing Method to Lessen k-Anonymity Dissimilarities
Protecting personal data is essential to guarantee the rule of law1 . Due to the new Information and Communication Technologies (ICTs) unprecedented amounts of personal data can b...
Agusti Solanas, Gloria Pujol, Antoni Martín...
TKDE
2002
127views more  TKDE 2002»
13 years 8 months ago
Efficient Join-Index-Based Spatial-Join Processing: A Clustering Approach
A join-index is a data structure used for processing join queries in databases. Join-indices use precomputation techniques to speed up online query processing and are useful for da...
Shashi Shekhar, Chang-Tien Lu, Sanjay Chawla, Siva...
SIGMOD
2000
ACM
165views Database» more  SIGMOD 2000»
14 years 1 months ago
Finding Generalized Projected Clusters In High Dimensional Spaces
High dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Recent research results indicate that in high dimension...
Charu C. Aggarwal, Philip S. Yu
ICML
2005
IEEE
14 years 10 months ago
Clustering through ranking on manifolds
Clustering aims to find useful hidden structures in data. In this paper we present a new clustering algorithm that builds upon the consistency method (Zhou, et.al., 2003), a semi-...
Markus Breitenbach, Gregory Z. Grudic