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ICDE
2006
IEEE
144views Database» more  ICDE 2006»
14 years 11 months ago
Super-Scalar RAM-CPU Cache Compression
High-performance data-intensive query processing tasks like OLAP, data mining or scientific data analysis can be severely I/O bound, even when high-end RAID storage systems are us...
Marcin Zukowski, Niels Nes, Peter A. Boncz, S&aacu...
SIGMOD
1999
ACM
110views Database» more  SIGMOD 1999»
14 years 2 months ago
Multi-dimensional Selectivity Estimation Using Compressed Histogram Information
The database query optimizer requires the estimation of the query selectivity to find the most efficient access plan. For queries referencing multiple attributes from the same rel...
Ju-Hong Lee, Deok-Hwan Kim, Chin-Wan Chung
KDD
1994
ACM
118views Data Mining» more  KDD 1994»
14 years 2 months ago
Discovering Informative Patterns and Data Cleaning
Wepresent a methodfor discovering informative patterns from data. With this method,large databases can be reducedto only a few representative data entries. Ourframeworkencompasses...
Isabelle Guyon, Nada Matic, Vladimir Vapnik
PKDD
1998
Springer
123views Data Mining» more  PKDD 1998»
14 years 2 months ago
Querying Inductive Databases: A Case Study on the MINE RULE Operator
Knowledge discovery in databases (KDD) is a process that can include steps like forming the data set, data transformations, discovery of patterns, searching for exceptions to a pat...
Jean-François Boulicaut, Mika Klemettinen, ...
CINQ
2004
Springer
157views Database» more  CINQ 2004»
14 years 2 months ago
Inductive Databases and Multiple Uses of Frequent Itemsets: The cInQ Approach
Inductive databases (IDBs) have been proposed to afford the problem of knowledge discovery from huge databases. With an IDB the user/analyst performs a set of very different operat...
Jean-François Boulicaut