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» Discovering and Processing Sequential Patterns in Databases
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SSD
2001
Springer
218views Database» more  SSD 2001»
15 years 2 months ago
Efficient Mining of Spatiotemporal Patterns
The problem of mining spatiotemporal patterns is finding sequences of events that occur frequently in spatiotemporal datasets. Spatiotemporal datasets store the evolution of object...
Ilias Tsoukatos, Dimitrios Gunopulos
70
Voted
FLAIRS
2008
14 years 12 months ago
Contrast Pattern Mining with Gap Constraints for Peptide Folding Prediction
1 In this paper, we propose a peptide folding prediction method which discovers contrast patterns to differentiate and predict peptide folding classes. A contrast pattern is defin...
Chinar C. Shah, Xingquan Zhu, Taghi M. Khoshgoftaa...
ICTAI
2003
IEEE
15 years 2 months ago
Parallel Mining of Maximal Frequent Itemsets from Databases
In this paper, we propose a parallel algorithm for mining maximal frequent itemsets from databases. A frequent itemset is maximal if none of its supersets is frequent. The new par...
Soon Myoung Chung, Congnan Luo
PAKDD
2004
ACM
199views Data Mining» more  PAKDD 2004»
15 years 3 months ago
Temporal Sequence Associations for Rare Events
In many real world applications, systematic analysis of rare events, such as credit card frauds and adverse drug reactions, is very important. Their low occurrence rate in large da...
Jie Chen, Hongxing He, Graham J. Williams, Huidong...
ISDA
2009
IEEE
15 years 4 months ago
From Local Patterns to Global Models: Towards Domain Driven Educational Process Mining
Educational process mining (EPM) aims at (i) constructing complete and compact educational process models that are able to reproduce all observed behavior (process model discovery...
Nikola Trcka, Mykola Pechenizkiy