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» Mining Data Streams under Block Evolution
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ICDM
2007
IEEE
140views Data Mining» more  ICDM 2007»
15 years 1 months ago
Sequential Change Detection on Data Streams
Model-based declarative queries are becoming an attractive paradigm for interacting with many data stream applications. This has led to the development of techniques to accurately...
S. Muthukrishnan, Eric van den Berg, Yihua Wu
SDM
2007
SIAM
131views Data Mining» more  SDM 2007»
14 years 11 months ago
Load Shedding in Classifying Multi-Source Streaming Data: A Bayes Risk Approach
In many applications, we monitor data obtained from multiple streaming sources for collective decision making. The task presents several challenges. First, data in sensor networks...
Yijian Bai, Haixun Wang, Carlo Zaniolo
ICDE
2007
IEEE
167views Database» more  ICDE 2007»
15 years 4 months ago
Load Shedding for Window Joins on Multiple Data Streams
We consider the problem of semantic load shedding for continuous queries containing window joins on multiple data streams and propose a robust approach that is effective with the ...
Yan-Nei Law, Carlo Zaniolo
COMAD
2009
14 years 11 months ago
Categorizing Concepts for Detecting Drifts in Stream
Mining evolving data streams for concept drifts has gained importance in applications like customer behavior analysis, network intrusion detection, credit card fraud detection. Se...
Sharanjit Kaur, Vasudha Bhatnagar, Sameep Mehta, S...
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
15 years 10 months ago
A fast algorithm for finding frequent episodes in event streams
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan