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» Practical Preference Relations for Large Data Sets
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STOC
2001
ACM
134views Algorithms» more  STOC 2001»
16 years 5 months ago
Data-streams and histograms
Histograms are typically used to approximate data distributions. Histograms and related synopsis structures have been successful in a wide variety of popular database applications...
Sudipto Guha, Nick Koudas, Kyuseok Shim
AIIA
2007
Springer
15 years 11 months ago
English Querying over Ontologies: E-QuOnto
Relational database (DB) management systems provide the standard means for structuring and querying large amounts of data. However, to access such data the exact structure of the D...
Raffaella Bernardi, Francesca Bonin, Diego Calvane...
VLDB
1998
ACM
105views Database» more  VLDB 1998»
15 years 9 months ago
Computing Iceberg Queries Efficiently
Many applications compute aggregate functions over an attribute (or set of attributes) to find aggregate values above some specified threshold. We call such queries iceberg querie...
Min Fang, Narayanan Shivakumar, Hector Garcia-Moli...
ICDM
2010
IEEE
226views Data Mining» more  ICDM 2010»
15 years 3 months ago
Edge Weight Regularization over Multiple Graphs for Similarity Learning
The growth of the web has directly influenced the increase in the availability of relational data. One of the key problems in mining such data is computing the similarity between o...
Pradeep Muthukrishnan, Dragomir R. Radev, Qiaozhu ...
SDM
2011
SIAM
241views Data Mining» more  SDM 2011»
14 years 8 months ago
A Fast Algorithm for Sparse PCA and a New Sparsity Control Criteria
Sparse principal component analysis (PCA) imposes extra constraints or penalty terms to the standard PCA to achieve sparsity. In this paper, we first introduce an efficient algor...
Yunlong He, Renato Monteiro, Haesun Park