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SDM
2010
SIAM
283views Data Mining» more  SDM 2010»
13 years 9 months ago
Cascading Spatio-temporal Pattern Discovery: A Summary of Results
Given a collection of Boolean spatio-temporal(ST) event types, the cascading spatio-temporal pattern (CSTP) discovery process finds partially ordered subsets of event-types whose ...
Pradeep Mohan, Shashi Shekhar, James A. Shine, Jam...
SDM
2004
SIAM
207views Data Mining» more  SDM 2004»
13 years 8 months ago
BAMBOO: Accelerating Closed Itemset Mining by Deeply Pushing the Length-Decreasing Support Constraint
Previous study has shown that mining frequent patterns with length-decreasing support constraint is very helpful in removing some uninteresting patterns based on the observation t...
Jianyong Wang, George Karypis
TKDE
1998
111views more  TKDE 1998»
13 years 7 months ago
Efficient Data Mining for Path Traversal Patterns
—In this paper, we explore a new data mining capability that involves mining path traversal patterns in a distributed information-providing environment where documents or objects...
Ming-Syan Chen, Jong Soo Park, Philip S. Yu
KDD
2008
ACM
217views Data Mining» more  KDD 2008»
14 years 8 months ago
Stream prediction using a generative model based on frequent episodes in event sequences
This paper presents a new algorithm for sequence prediction over long categorical event streams. The input to the algorithm is a set of target event types whose occurrences we wis...
Srivatsan Laxman, Vikram Tankasali, Ryen W. White
SDM
2009
SIAM
175views Data Mining» more  SDM 2009»
14 years 4 months ago
Low-Entropy Set Selection.
Most pattern discovery algorithms easily generate very large numbers of patterns, making the results impossible to understand and hard to use. Recently, the problem of instead sel...
Hannes Heikinheimo, Jilles Vreeken, Arno Siebes, H...