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» kDCI: a Multi-Strategy Algorithm for Mining Frequent Sets
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KDD
2009
ACM
239views Data Mining» more  KDD 2009»
14 years 9 months ago
Tell me something I don't know: randomization strategies for iterative data mining
There is a wide variety of data mining methods available, and it is generally useful in exploratory data analysis to use many different methods for the same dataset. This, however...
Heikki Mannila, Kai Puolamäki, Markus Ojala, ...
SP
2008
IEEE
159views Security Privacy» more  SP 2008»
13 years 8 months ago
Inferring neuronal network connectivity from spike data: A temporal data mining approach
Abstract. Understanding the functioning of a neural system in terms of its underlying circuitry is an important problem in neuroscience. Recent developments in electrophysiology an...
Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishn...
MMM
2007
Springer
114views Multimedia» more  MMM 2007»
14 years 2 months ago
Mining Multiple Visual Appearances of Semantics for Image Annotation
This paper investigates the problem of learning the visual semantics of keyword categories for automatic image annotation. Supervised learning algorithms which learn only a single ...
Hung-Khoon Tan, Chong-Wah Ngo
DMIN
2006
126views Data Mining» more  DMIN 2006»
13 years 10 months ago
An Algorithm for the Discovery of Arbitrary Length Ordinal Association Rules
Association rule mining techniques are used to search attribute-value pairs that occur frequently together in a data set. Ordinal association rules are a particular type of associa...
Alina Campan, Gabriela Serban, Traian Marius Truta...
PKDD
1999
Springer
272views Data Mining» more  PKDD 1999»
14 years 25 days ago
Handling Missing Data in Trees: Surrogate Splits or Statistical Imputation
Abstract. In many applications of data mining a - sometimes considerable - part of the data values is missing. This may occur because the data values were simply never entered into...
A. J. Feelders