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PKDD
2005
Springer
101views Data Mining» more  PKDD 2005»
14 years 4 months ago
A Random Method for Quantifying Changing Distributions in Data Streams
In applications such as fraud and intrusion detection, it is of great interest to measure the evolving trends in the data. We consider the problem of quantifying changes between tw...
Haixun Wang, Jian Pei
VLDB
2004
ACM
129views Database» more  VLDB 2004»
14 years 4 months ago
Detecting Change in Data Streams
Detecting changes in a data stream is an important area of research with many applications. In this paper, we present a novel method for the detection and estimation of change. In...
Daniel Kifer, Shai Ben-David, Johannes Gehrke
INFORMATICALT
2008
196views more  INFORMATICALT 2008»
13 years 11 months ago
An Efficient and Sensitive Decision Tree Approach to Mining Concept-Drifting Data Streams
Abstract. Data stream mining has become a novel research topic of growing interest in knowledge discovery. Most proposed algorithms for data stream mining assume that each data blo...
Cheng-Jung Tsai, Chien-I Lee, Wei-Pang Yang
ICDM
2007
IEEE
140views Data Mining» more  ICDM 2007»
14 years 3 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
EUROGP
2007
Springer
161views Optimization» more  EUROGP 2007»
14 years 5 months ago
Mining Distributed Evolving Data Streams Using Fractal GP Ensembles
A Genetic Programming based boosting ensemble method for the classification of distributed streaming data is proposed. The approach handles flows of data coming from multiple loc...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...