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ACSW
2004
13 years 6 months ago
Cost-Efficient Mining Techniques for Data Streams
A data stream is a continuous and high-speed flow of data items. High speed refers to the phenomenon that the data rate is high relative to the computational power. The increasing...
Mohamed Medhat Gaber, Shonali Krishnaswamy, Arkady...
KDD
2009
ACM
217views Data Mining» more  KDD 2009»
14 years 5 months ago
Efficient anomaly monitoring over moving object trajectory streams
Lately there exist increasing demands for online abnormality monitoring over trajectory streams, which are obtained from moving object tracking devices. This problem is challengin...
Yingyi Bu, Lei Chen 0002, Ada Wai-Chee Fu, Dawei L...
CCGRID
2006
IEEE
13 years 10 months ago
Calder Query Grid Service: Insights and Experimental Evaluation
We have architected and evaluated a new kind of data resource, one that is composed of a logical collection of ephemeral data streams that could be viewed as a collection of publi...
Nithya N. Vijayakumar, Ying Liu, Beth Plale
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
14 years 5 months ago
Density-based clustering for real-time stream data
Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...
Yixin Chen, Li Tu
IJCAI
2007
13 years 6 months ago
Detecting Changes in Unlabeled Data Streams Using Martingale
The martingale framework for detecting changes in data stream, currently only applicable to labeled data, is extended here to unlabeled data using clustering concept. The one-pass...
Shen-Shyang Ho, Harry Wechsler