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» Mining Multiple Large Databases
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KDD
2002
ACM
138views Data Mining» more  KDD 2002»
14 years 8 months ago
Learning to match and cluster large high-dimensional data sets for data integration
Part of the process of data integration is determining which sets of identifiers refer to the same real-world entities. In integrating databases found on the Web or obtained by us...
William W. Cohen, Jacob Richman
MTA
2006
173views more  MTA 2006»
13 years 7 months ago
Active learning in very large databases
Abstract. Query-by-example and query-by-keyword both suffer from the problem of "aliasing," meaning that example-images and keywords potentially have variable interpretat...
Navneet Panda, Kingshy Goh, Edward Y. Chang
DAWAK
2006
Springer
13 years 11 months ago
A Greedy Approach to Concurrent Processing of Frequent Itemset Queries
We consider the problem of concurrent execution of multiple frequent itemset queries. If such data mining queries operate on overlapping parts of the database, then their overall I...
Pawel Boinski, Marek Wojciechowski, Maciej Zakrzew...
GECCO
2008
Springer
232views Optimization» more  GECCO 2008»
13 years 8 months ago
An efficient SVM-GA feature selection model for large healthcare databases
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...
DAWAK
2001
Springer
14 years 4 days ago
Determining the Convex Hull in Large Multidimensional Databases
Determiningthe convex hull ofa point set isa basic operation for many applications of pattern recognition, image processing, statistics, and data mining. Although the corresponding...
Christian Böhm, Hans-Peter Kriegel