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» Mining Supplemental Frequent Patterns
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HICSS
2003
IEEE
171views Biometrics» more  HICSS 2003»
14 years 3 months ago
Improving the Efficiency of Interactive Sequential Pattern Mining by Incremental Pattern Discovery
The discovery of sequential patterns, which extends beyond frequent item-set finding of association rule mining, has become a challenging task due to its complexity. Essentially, ...
Ming-Yen Lin, Suh-Yin Lee
IFIP12
2007
13 years 11 months ago
Clustering Improves the Exploration of Graph Mining Results
Mining frequent subgraphs is an area of research where we have a given set of graphs, and where we search for (connected) subgraphs contained in many of these graphs. Each graph ca...
Edgar H. de Graaf, Joost N. Kok, Walter A. Kosters
EDBT
2011
ACM
199views Database» more  EDBT 2011»
13 years 1 months ago
Finding closed frequent item sets by intersecting transactions
Most known frequent item set mining algorithms work by enumerating candidate item sets and pruning infrequent candidates. An alternative method, which works by intersecting transa...
Christian Borgelt, Xiaoyuan Yang, Rubén Nog...
PAKDD
2010
ACM
152views Data Mining» more  PAKDD 2010»
14 years 2 months ago
Mining Association Rules in Long Sequences
Abstract. Discovering interesting patterns in long sequences, and finding confident association rules within them, is a popular area in data mining. Most existing methods define...
Boris Cule, Bart Goethals
KDD
1998
ACM
105views Data Mining» more  KDD 1998»
14 years 2 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