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» Memory Prefetching Using Adaptive Stream Detection
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DASFAA
2008
IEEE
149views Database» more  DASFAA 2008»
13 years 8 months ago
A Test Paradigm for Detecting Changes in Transactional Data Streams
A pattern is considered useful if it can be used to help a person to achieve his goal. Mining data streams for useful patterns is important in many applications. However, data stre...
Willie Ng, Manoranjan Dash
CIKM
2010
Springer
13 years 6 months ago
Partial drift detection using a rule induction framework
The major challenge in mining data streams is the issue of concept drift, the tendency of the underlying data generation process to change over time. In this paper, we propose a g...
Damon Sotoudeh, Aijun An
WWW
2009
ACM
14 years 2 months ago
A general framework for adaptive and online detection of web attacks
Detection of web attacks is an important issue in current defense-in-depth security framework. In this paper, we propose a novel general framework for adaptive and online detectio...
Wei Wang 0012, Florent Masseglia, Thomas Guyet, Re...
IEEEHPCS
2010
13 years 5 months ago
Reducing memory requirements of stream programs by graph transformations
Stream languages explicitly describe fork-join parallelism and pipelines, offering a powerful programming model for many-core Multi-Processor Systems on Chip (MPSoC). In an embedd...
Pablo de Oliveira Castro, Stéphane Louise, ...
KDD
2003
ACM
194views Data Mining» more  KDD 2003»
14 years 8 months ago
Finding recent frequent itemsets adaptively over online data streams
A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Consequently, the knowledge embedded in a data stream is more likely to be c...
Joong Hyuk Chang, Won Suk Lee