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KDD
1999
ACM
108views Data Mining» more  KDD 1999»
15 years 9 months ago
Mining the Most Interesting Rules
Several algorithms have been proposed for finding the “best,” “optimal,” or “most interesting” rule(s) in a database according to a variety of metrics including confid...
Roberto J. Bayardo Jr., Rakesh Agrawal
ICDM
2007
IEEE
132views Data Mining» more  ICDM 2007»
15 years 11 months ago
Error-Aware Density-Based Clustering of Imprecise Measurement Values
Manufacturing process development is under constant pressure to achieve a good yield for stable processes. The development of new technologies, especially in the field of photoma...
Dirk Habich, Peter Benjamin Volk, Wolfgang Lehner,...
BIODATAMINING
2008
120views more  BIODATAMINING 2008»
15 years 5 months ago
Filling the gap between biology and computer science
This editorial introduces BioData Mining, a new journal which publishes research articles related to advances in computational methods and techniques for the extraction of useful ...
Jesús S. Aguilar-Ruiz, Jason H. Moore, Mary...
ICDM
2003
IEEE
141views Data Mining» more  ICDM 2003»
15 years 10 months ago
Association Rule Mining in Peer-to-Peer Systems
We extend the problem of association rule mining – a key data mining problem – to systems in which the database is partitioned among a very large number of computers that are ...
Ran Wolff, Assaf Schuster
SDM
2004
SIAM
141views Data Mining» more  SDM 2004»
15 years 6 months ago
Visually Mining through Cluster Hierarchies
Similarity search in database systems is becoming an increasingly important task in modern application domains such as multimedia, molecular biology, medical imaging, computer aid...
Stefan Brecheisen, Hans-Peter Kriegel, Peer Kr&oum...