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KDD
2004
ACM
211views Data Mining» more  KDD 2004»
16 years 7 months ago
Towards parameter-free data mining
Most data mining algorithms require the setting of many input parameters. Two main dangers of working with parameter-laden algorithms are the following. First, incorrect settings ...
Eamonn J. Keogh, Stefano Lonardi, Chotirat (Ann) R...
KDD
2003
ACM
205views Data Mining» more  KDD 2003»
16 years 7 months ago
The data mining approach to automated software testing
In today's industry, the design of software tests is mostly based on the testers' expertise, while test automation tools are limited to execution of pre-planned tests on...
Mark Last, Menahem Friedman, Abraham Kandel
SIGMOD
2004
ACM
209views Database» more  SIGMOD 2004»
16 years 6 months ago
MAIDS: Mining Alarming Incidents from Data Streams
Real-time surveillance systems, network and telecommunication systems, and other dynamic processes often generate tremendous (potentially infinite) volume of stream data. Effectiv...
Y. Dora Cai, David Clutter, Greg Pape, Jiawei Han,...
SDM
2009
SIAM
219views Data Mining» more  SDM 2009»
16 years 3 months ago
A Hybrid Data Mining Metaheuristic for the p-Median Problem.
Metaheuristics represent an important class of techniques to solve, approximately, hard combinatorial optimization problems for which the use of exact methods is impractical. In t...
Alexandre Plastino, Erick R. Fonseca, Richard Fuch...
ICDM
2008
IEEE
137views Data Mining» more  ICDM 2008»
16 years 1 months ago
Stream Sequential Pattern Mining with Precise Error Bounds
Sequential pattern mining is an interesting data mining problem with many real-world applications. This problem has been studied extensively in static databases. However, in recen...
Luiz F. Mendes, Bolin Ding, Jiawei Han