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» Approximated Clustering of Distributed High-Dimensional Data
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SDM
2004
SIAM
162views Data Mining» more  SDM 2004»
13 years 6 months ago
Subspace Clustering of High Dimensional Data
Clustering suffers from the curse of dimensionality, and similarity functions that use all input features with equal relevance may not be effective. We introduce an algorithm that...
Carlotta Domeniconi, Dimitris Papadopoulos, Dimitr...
SSD
2005
Springer
122views Database» more  SSD 2005»
13 years 10 months ago
Selectivity Estimation of High Dimensional Window Queries via Clustering
Abstract. Query optimization is an important functionality of modern database systems and often based on estimating the selectivity of queries before actually executing them. Well-...
Christian Böhm, Hans-Peter Kriegel, Peer Kr&o...
SIGMOD
2001
ACM
104views Database» more  SIGMOD 2001»
14 years 5 months ago
Independence is Good: Dependency-Based Histogram Synopses for High-Dimensional Data
Approximating the joint data distribution of a multi-dimensional data set through a compact and accurate histogram synopsis is a fundamental problem arising in numerous practical ...
Amol Deshpande, Minos N. Garofalakis, Rajeev Rasto...
ICDE
2000
IEEE
168views Database» more  ICDE 2000»
14 years 6 months ago
PAC Nearest Neighbor Queries: Approximate and Controlled Search in High-Dimensional and Metric Spaces
In high-dimensional and complex metric spaces, determining the nearest neighbor (NN) of a query object ? can be a very expensive task, because of the poor partitioning operated by...
Paolo Ciaccia, Marco Patella
DEXA
2006
Springer
190views Database» more  DEXA 2006»
13 years 8 months ago
High-Dimensional Similarity Search Using Data-Sensitive Space Partitioning
Abstract. Nearest neighbor search has a wide variety of applications. Unfortunately, the majority of search methods do not scale well with dimensionality. Recent efforts have been ...
Sachin Kulkarni, Ratko Orlandic