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» kDCI: a Multi-Strategy Algorithm for Mining Frequent Sets
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CORR
2010
Springer
185views Education» more  CORR 2010»
14 years 6 months ago
Analysing the behaviour of robot teams through relational sequential pattern mining
This report outlines the use of a relational representation in a Multi-Agent domain to model the behaviour of the whole system. A desired property in this systems is the ability of...
Grazia Bombini, Raquel Ros, Stefano Ferilli, Ramon...
KDD
2007
ACM
165views Data Mining» more  KDD 2007»
15 years 10 months ago
Finding low-entropy sets and trees from binary data
The discovery of subsets with special properties from binary data has been one of the key themes in pattern discovery. Pattern classes such as frequent itemsets stress the co-occu...
Eino Hinkkanen, Hannes Heikinheimo, Heikki Mannila...
CINQ
2004
Springer
131views Database» more  CINQ 2004»
15 years 3 months ago
Model-Independent Bounding of the Supports of Boolean Formulae in Binary Data
Abstract. Data mining algorithms such as the Apriori method for finding frequent sets in sparse binary data can be used for efficient computation of a large number of summaries fr...
Artur Bykowski, Jouni K. Seppänen, Jaakko Hol...
KDD
1998
ACM
105views Data Mining» more  KDD 1998»
15 years 1 months ago
PlanMine: Sequence Mining for Plan Failures
This paper presents the PLANMINE sequence mining algorithm to extract patterns of events that predict failures in databases of plan executions. New techniques were needed because ...
Mohammed Javeed Zaki, Neal Lesh, Mitsunori Ogihara
RSFDGRC
2005
Springer
110views Data Mining» more  RSFDGRC 2005»
15 years 3 months ago
A Rough Set Based Model to Rank the Importance of Association Rules
Abstract. Association rule algorithms often generate an excessive number of rules, many of which are not significant. It is difficult to determine which rules are more useful, int...
Jiye Li, Nick Cercone