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» A Data Stream Mining System
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CN
2006
163views more  CN 2006»
13 years 7 months ago
A framework for mining evolving trends in Web data streams using dynamic learning and retrospective validation
The expanding and dynamic nature of the Web poses enormous challenges to most data mining techniques that try to extract patterns from Web data, such as Web usage and Web content....
Olfa Nasraoui, Carlos Rojas, Cesar Cardona
EPIA
2003
Springer
14 years 26 days ago
Mining Low Dimensionality Data Streams of Continuous Attributes
This paper presents an incremental and scalable learning algorithm in order to mine numeric, low dimensionality, high–cardinality, time–changing data streams. Within the Superv...
Francisco J. Ferrer-Troyano, Jesús S. Aguil...
KDD
2006
ACM
129views Data Mining» more  KDD 2006»
14 years 8 months ago
Suppressing model overfitting in mining concept-drifting data streams
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jef...
PAKDD
2004
ACM
137views Data Mining» more  PAKDD 2004»
14 years 1 months ago
Fast and Light Boosting for Adaptive Mining of Data Streams
Supporting continuous mining queries on data streams requires algorithms that (i) are fast, (ii) make light demands on memory resources, and (iii) are easily to adapt to concept dr...
Fang Chu, Carlo Zaniolo
ICTAI
2007
IEEE
14 years 1 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...