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» Info-fuzzy algorithms for mining dynamic data streams
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AUSDM
2006
Springer
94views Data Mining» more  AUSDM 2006»
15 years 8 months ago
Marking Time in Sequence Mining
Sequence mining is often conducted over static and temporal datasets as well as over collections of events (episodes). More recently, there has also been a focus on the mining of ...
Carl Mooney, John F. Roddick
KDD
2003
ACM
170views Data Mining» more  KDD 2003»
16 years 4 months ago
Efficient decision tree construction on streaming data
Decision tree construction is a well studied problem in data mining. Recently, there has been much interest in mining streaming data. Domingos and Hulten have presented a one-pass...
Ruoming Jin, Gagan Agrawal
ICDM
2007
IEEE
140views Data Mining» more  ICDM 2007»
15 years 8 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»
15 years 5 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
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
16 years 4 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