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» Efficient Multidimensional Sampling
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KDD
2001
ACM
253views Data Mining» more  KDD 2001»
16 years 5 months ago
GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
Jens-Peter Dittrich, Bernhard Seeger
KDD
2001
ACM
203views Data Mining» more  KDD 2001»
16 years 5 months ago
Ensemble-index: a new approach to indexing large databases
The problem of similarity search (query-by-content) has attracted much research interest. It is a difficult problem because of the inherently high dimensionality of the data. The ...
Eamonn J. Keogh, Selina Chu, Michael J. Pazzani
SIGMOD
2008
ACM
193views Database» more  SIGMOD 2008»
16 years 5 months ago
ARCube: supporting ranking aggregate queries in partially materialized data cubes
Supporting ranking queries in database systems has been a popular research topic recently. However, there is a lack of study on supporting ranking queries in data warehouses where...
Tianyi Wu, Dong Xin, Jiawei Han
SIGMOD
2008
ACM
215views Database» more  SIGMOD 2008»
16 years 5 months ago
CSV: visualizing and mining cohesive subgraphs
Extracting dense sub-components from graphs efficiently is an important objective in a wide range of application domains ranging from social network analysis to biological network...
Nan Wang, Srinivasan Parthasarathy, Kian-Lee Tan, ...
ICPADS
2005
IEEE
15 years 10 months ago
A Model for Distributing and Querying a Data Warehouse on a Computing Grid
Data warehouses store large volumes of data according to a multidimensional model with dimensions representing different axes of analysis. OLAP systems (OnLine Analytical Processi...
Pascal Wehrle, Maryvonne Miquel, Anne Tchounikine