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» Real world performance of association rule algorithms
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KDD
2002
ACM
140views Data Mining» more  KDD 2002»
15 years 10 months ago
Mining frequent item sets by opportunistic projection
In this paper, we present a novel algorithm OpportuneProject for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. Our algorithm ...
Junqiang Liu, Yunhe Pan, Ke Wang, Jiawei Han
ICIP
2009
IEEE
15 years 10 months ago
M2sir: A Multi Modal Sequential Importance Resampling Algorithm For Particle Filters
We present a multi modal sequential importance resampling particle filter algorithm for object tracking. We consider a hidden state sequence linked to several observation sequence...
KDD
2003
ACM
156views Data Mining» more  KDD 2003»
15 years 10 months ago
Mining distance-based outliers in near linear time with randomization and a simple pruning rule
Defining outliers by their distance to neighboring examples is a popular approach to finding unusual examples in a data set. Recently, much work has been conducted with the goal o...
Stephen D. Bay, Mark Schwabacher
NAA
2004
Springer
178views Mathematics» more  NAA 2004»
15 years 3 months ago
Performance Optimization and Evaluation for Linear Codes
In this paper, we develop a probabilistic model for estimation of the numbers of cache misses during the sparse matrix-vector multiplication (for both general and symmetric matrice...
Pavel Tvrdík, Ivan Simecek
DAWAK
2010
Springer
14 years 10 months ago
Mining Closed Itemsets in Data Stream Using Formal Concept Analysis
Mining of frequent closed itemsets has been shown to be more efficient than mining frequent itemsets for generating non-redundant association rules. The task is challenging in data...
Anamika Gupta, Vasudha Bhatnagar, Naveen Kumar