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IS
2007
14 years 9 months ago
Mining association rules in very large clustered domains
Emerging applications introduce the requirement for novel association-rule mining algorithms that will be scalable not only with respect to the number of records (number of rows) ...
Alexandros Nanopoulos, Apostolos N. Papadopoulos, ...
77
Voted
CIKM
2003
Springer
15 years 3 months ago
Dimensionality reduction using magnitude and shape approximations
High dimensional data sets are encountered in many modern database applications. The usual approach is to construct a summary of the data set through a lossy compression technique...
Ümit Y. Ogras, Hakan Ferhatosmanoglu
CEC
2003
IEEE
15 years 3 months ago
Learning DFA: evolution versus evidence driven state merging
Learning Deterministic Finite Automata (DFA) is a hard task that has been much studied within machine learning and evolutionary computation research. This paper presents a new met...
Simon M. Lucas, T. Jeff Reynolds
ENTCS
2008
132views more  ENTCS 2008»
14 years 9 months ago
Distributed Verification of Multi-threaded C++ Programs
Verification of multi-threaded C++ programs poses three major challenges: the large number of states, states with huge sizes, and time intensive expansions of states. This paper p...
Stefan Edelkamp, Shahid Jabbar, Damian Sulewski
KDD
1998
ACM
145views Data Mining» more  KDD 1998»
15 years 2 months ago
Coincidence Detection: A Fast Method for Discovering Higher-Order Correlations in Multidimensional Data
Wepresent a novel, fast methodfor associationminingill high-dimensionaldatasets. OurCoincidence Detection method, which combines random sampling and Chernoff-Hoeffding bounds with...
Evan W. Steeg, Derek A. Robinson, Ed Willis