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» Efficient frequent pattern mining over data streams
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KDD
2008
ACM
243views Data Mining» more  KDD 2008»
15 years 10 months ago
Permu-pattern: discovery of mutable permutation patterns with proximity constraint
Pattern discovery in sequences is an important problem in many applications, especially in computational biology and text mining. However, due to the noisy nature of data, the tra...
Meng Hu, Jiong Yang, Wei Su
ICML
1996
IEEE
15 years 10 months ago
Searching for Structure in Multiple Streams of Data
Finding structure in multiple streams of data is an important problem. Consider the streams of data owing from a robot's sensors, the monitors in an intensive care unit, or p...
Tim Oates, Paul R. Cohen
ICTAI
2007
IEEE
15 years 4 months ago
An Adaptive Distributed Ensemble Approach to Mine Concept-Drifting Data Streams
An adaptive boosting ensemble algorithm for classifying homogeneous distributed data streams is presented. The method builds an ensemble of classifiers by using Genetic Programmi...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
15 years 10 months ago
Mining concept-drifting data streams using ensemble classifiers
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
Haixun Wang, Wei Fan, Philip S. Yu, Jiawei Han
ICSNC
2007
IEEE
15 years 4 months ago
Efficient Transformation Scheme for Indexing Continuous Queries on RFID Streaming Data
RFID data are usually regarded as streaming data that are huge and change frequently because they are gathered continuously by numerous readers. RFID middleware filters the data a...
Jaekwan Park, Bonghee Hong, ChaeHoon Ban