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» Efficient Discovery of Confounders in Large Data Sets
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KDD
1999
ACM
220views Data Mining» more  KDD 1999»
15 years 10 months ago
Efficient Mining of Emerging Patterns: Discovering Trends and Differences
We introduce a new kind of patterns, called emerging patterns (EPs), for knowledge discovery from databases. EPs are defined as itemsets whose supports increase significantly from...
Guozhu Dong, Jinyan Li
CGF
2010
171views more  CGF 2010»
15 years 2 months ago
Efficient Mean-shift Clustering Using Gaussian KD-Tree
Mean shift is a popular approach for data clustering, however, the high computational complexity of the mean shift procedure limits its practical applications in high dimensional ...
Chunxia Xiao, Meng Liu
CSSW
2007
15 years 7 months ago
Discovering Unknown Connections - the DBpedia Relationship Finder
: The Relationship Finder is a tool for exploring connections between objects in a Semantic Web knowledge base. It offers a new way to get insights about elements in an ontology, i...
Jens Lehmann, Jörg Schüppel, Sören ...
KDD
1997
ACM
92views Data Mining» more  KDD 1997»
15 years 10 months ago
Increasing the Efficiency of Data Mining Algorithms with Breadth-First Marker Propagation
This paper describes how to increase the efficiency of inductive data mining algorithms by replacing the central matching operation with a marker propagation technique. Breadth-fi...
John M. Aronis, Foster J. Provost
AMAI
2007
Springer
15 years 6 months ago
Relational concept discovery in structured datasets
Relational datasets, i.e., datasets in which individuals are described both by their own features and by their relations to other individuals, arise from various sources such as d...
Marianne Huchard, Mohamed Rouane Hacene, Cyril Rou...