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» Methods for finding frequent items in data streams
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CVPR
2008
IEEE
13 years 9 months ago
A rank constrained continuous formulation of multi-frame multi-target tracking problem
This paper presents a multi-frame data association algorithm for tracking multiple targets in video sequences. Multi-frame data association involves finding the most probable corr...
Khurram Shafique, Mun Wai Lee, Niels Haering
KDD
2006
ACM
109views Data Mining» more  KDD 2006»
14 years 8 months ago
Extracting redundancy-aware top-k patterns
Observed in many applications, there is a potential need of extracting a small set of frequent patterns having not only high significance but also low redundancy. The significance...
Dong Xin, Hong Cheng, Xifeng Yan, Jiawei Han
WAIM
2010
Springer
13 years 6 months ago
Mining Contrast Inequalities in Numeric Dataset
Finding relational expressions which exist frequently in one class of data while not in the other class of data is an interesting work. In this paper, a relational expression of th...
Lei Duan, Jie Zuo, Tianqing Zhang, Jing Peng, Jie ...
HPDC
2008
IEEE
13 years 7 months ago
Code coverage, performance approximation and automatic recognition of idioms in scientific applications
Basic data flow patterns which we call idioms, such as stream, transpose, reduction, random access and stencil, are common in scientific numerical applications. We hypothesize tha...
Jiahua He, Allan Snavely, Rob F. Van der Wijngaart...
CIKM
2005
Springer
14 years 1 months ago
Opportunity map: a visualization framework for fast identification of actionable knowledge
Data mining techniques frequently find a large number of patterns or rules, which make it very difficult for a human analyst to interpret the results and to find the truly interes...
Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Weimin Xia...