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» Mining Very Large Databases
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110
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DEXA
2005
Springer
110views Database» more  DEXA 2005»
15 years 8 months ago
Intensional Encapsulations of Database Subsets via Genetic Programming
Finding intensional encapsulations of database subsets is the inverse of query evaluation. Whereas query evaluation transforms an intensional expression (the query) to its extensi...
Aybar C. Acar, Amihai Motro
VLDB
2007
ACM
179views Database» more  VLDB 2007»
16 years 2 months ago
Mining Approximate Top-K Subspace Anomalies in Multi-Dimensional Time-Series Data
Market analysis is a representative data analysis process with many applications. In such an analysis, critical numerical measures, such as profit and sales, fluctuate over time a...
Xiaolei Li, Jiawei Han
175
Voted
ESANN
2004
15 years 4 months ago
Data Mining Techniques on the Evaluation of Wireless Churn
This work focuses on one of the most critical issues to plague the wireless telecommunications industry today: the loss of a valuable subscriber to a competitor, also defined as ch...
Jorge Ferreira, Marley B. R. Vellasco, Marco Aur&e...
138
Voted
PKDD
2007
Springer
76views Data Mining» more  PKDD 2007»
15 years 8 months ago
Experiment Databases: Towards an Improved Experimental Methodology in Machine Learning
Machine learning research often has a large experimental component. While the experimental methodology employed in machine learning has improved much over the years, repeatability ...
Hendrik Blockeel, Joaquin Vanschoren
239
Voted
ICDE
2003
IEEE
146views Database» more  ICDE 2003»
16 years 4 months ago
Generalized Closed Itemsets for Association Rule Mining
The output of boolean association rule mining algorithms is often too large for manual examination. For dense datasets, it is often impractical to even generate all frequent items...
Vikram Pudi, Jayant R. Haritsa