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KDD
2006
ACM
150views Data Mining» more  KDD 2006»
16 years 7 months ago
Maximally informative k-itemsets and their efficient discovery
In this paper we present a new approach to mining binary data. We treat each binary feature (item) as a means of distinguishing two sets of examples. Our interest is in selecting ...
Arno J. Knobbe, Eric K. Y. Ho
189
Voted
SDM
2004
SIAM
141views Data Mining» more  SDM 2004»
15 years 8 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...
KDD
2003
ACM
156views Data Mining» more  KDD 2003»
16 years 7 months ago
Mining distance-based outliers in near linear time with randomization and a simple pruning rule
Defining outliers by their distance to neighboring examples is a popular approach to finding unusual examples in a data set. Recently, much work has been conducted with the goal o...
Stephen D. Bay, Mark Schwabacher
ICDM
2003
IEEE
136views Data Mining» more  ICDM 2003»
15 years 12 months ago
Statistical Relational Learning for Document Mining
A major obstacle to fully integrated deployment of many data mining algorithms is the assumption that data sits in a single table, even though most real-world databases have compl...
Alexandrin Popescul, Lyle H. Ungar, Steve Lawrence...
JMLR
2010
119views more  JMLR 2010»
15 years 1 months ago
The Coding Divergence for Measuring the Complexity of Separating Two Sets
In this paper we integrate two essential processes, discretization of continuous data and learning of a model that explains them, towards fully computational machine learning from...
Mahito Sugiyama, Akihiro Yamamoto