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» New ensemble methods for evolving data streams
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ICDM
2008
IEEE
137views Data Mining» more  ICDM 2008»
14 years 3 months ago
Stream Sequential Pattern Mining with Precise Error Bounds
Sequential pattern mining is an interesting data mining problem with many real-world applications. This problem has been studied extensively in static databases. However, in recen...
Luiz F. Mendes, Bolin Ding, Jiawei Han
ICDM
2007
IEEE
254views Data Mining» more  ICDM 2007»
14 years 2 months ago
Sampling for Sequential Pattern Mining: From Static Databases to Data Streams
Sequential pattern mining is an active field in the domain of knowledge discovery. Recently, with the constant progress in hardware technologies, real-world databases tend to gro...
Chedy Raïssi, Pascal Poncelet
SIGMOD
2004
ACM
188views Database» more  SIGMOD 2004»
14 years 8 months ago
Online Event-driven Subsequence Matching over Financial Data Streams
Subsequence similarity matching in time series databases is an important research area for many applications. This paper presents a new approximate approach for automatic online s...
Huanmei Wu, Betty Salzberg, Donghui Zhang
DEBS
2008
ACM
13 years 10 months ago
Real-time, load-adaptive processing of continuous queries over data streams
We introduce a new type of query, called a real-time continuous query (RCQ), that captures the real-time requirements of processing data streams. We develop techniques to efficien...
Dhananjay Kulkarni, Chinya V. Ravishankar, Mitch C...
ICDE
2010
IEEE
188views Database» more  ICDE 2010»
14 years 8 months ago
Space-efficient Online Approximation of Time Series Data: Streams, Amnesia, and Out-of-order
In this paper, we present an abstract framework for online approximation of time-series data that yields a unified set of algorithms for several popular models: data streams, amnes...
Sorabh Gandhi, Luca Foschini, Subhash Suri