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ICDM
2007
IEEE
95views Data Mining» more  ICDM 2007»
15 years 4 months ago
Incremental Quantization for Aging Data Streams
A growing number of applications have become reliant or can benefit from monitoring data streams. Data streams are potentially unbounded in size, hence, Data Stream Management Sy...
Fatih Altiparmak, David Chiu, Hakan Ferhatosmanogl...
AUSDM
2007
Springer
145views Data Mining» more  AUSDM 2007»
15 years 4 months ago
Discovering Frequent Sets from Data Streams with CPU Constraint
Data streams are usually generated in an online fashion characterized by huge volume, rapid unpredictable rates, and fast changing data characteristics. It has been hence recogniz...
Xuan Hong Dang, Wee Keong Ng, Kok-Leong Ong, Vince...
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
15 years 10 months ago
Density-based clustering for real-time stream data
Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...
Yixin Chen, Li Tu
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
IDEAS
2008
IEEE
114views Database» more  IDEAS 2008»
15 years 4 months ago
Incremental view-based analysis of stock market data streams
In this paper we show the usefulness and feasibility of applying conventional SQL queries for analyzing a wide spectrum of data streams. As application area we have chosen the ana...
Andreas Behrend, Christian Dorau, Rainer Manthey, ...