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» Adaptive Learning from Evolving Data Streams
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KDD
2005
ACM
147views Data Mining» more  KDD 2005»
14 years 27 days ago
Combining proactive and reactive predictions for data streams
Mining data streams is important in both science and commerce. Two major challenges are (1) the data may grow without limit so that it is difficult to retain a long history; and (...
Ying Yang, Xindong Wu, Xingquan Zhu
ICDCS
2000
IEEE
13 years 11 months ago
An Adaptive, Perception-Driven Error Spreading Scheme in Continuous Media Streaming
For transmission of continuous media (CM) streams such as audio and video over the Internet, a critical issue is that periodic network overloads cause bursty packet losses. Studie...
Srivatsan Varadarajan, Hung Q. Ngo, Jaideep Srivas...
SAC
2006
ACM
14 years 1 months ago
Discretization from data streams: applications to histograms and data mining
Abstract. In this paper we propose a new method to perform incremental discretization. The basic idea is to perform the task in two layers. The first layer receives the sequence o...
João Gama, Carlos Pinto
SDM
2009
SIAM
208views Data Mining» more  SDM 2009»
14 years 4 months ago
Topic Evolution in a Stream of Documents.
Document collections evolve over time, new topics emerge and old ones decline. At the same time, the terminology evolves as well. Much literature is devoted to topic evolution in ...
Alexander Hinneburg, Andrè Gohr, Myra Spili...
IDEAS
2007
IEEE
148views Database» more  IDEAS 2007»
14 years 1 months ago
Adaptive Execution of Stream Window Joins in a Limited Memory Environment
A sliding window join (SWJoin) is becoming an integral operation in every stream data management system. In some streaming applications the increasing volume of streamed data as w...
Fatima Farag, Moustafa A. Hammad