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» Data streams: algorithms and applications
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97
Voted
KDD
2009
ACM
187views Data Mining» more  KDD 2009»
15 years 10 months ago
New ensemble methods for evolving data streams
Advanced analysis of data streams is quickly becoming a key area of data mining research as the number of applications demanding such processing increases. Online mining when such...
Albert Bifet, Bernhard Pfahringer, Geoffrey Holmes...
105
Voted
KDD
2007
ACM
152views Data Mining» more  KDD 2007»
15 years 10 months ago
A framework for classification and segmentation of massive audio data streams
In recent years, the proliferation of VOIP data has created a number of applications in which it is desirable to perform quick online classification and recognition of massive voi...
Charu C. Aggarwal
89
Voted
JCST
2008
121views more  JCST 2008»
14 years 10 months ago
Clustering Text Data Streams
Abstract Clustering text data streams is an important issue in data mining community and has a number of applications such as news group filtering, text crawling, document organiza...
Yubao Liu, Jiarong Cai, Jian Yin, Ada Wai-Chee Fu
76
Voted
ICDM
2010
IEEE
115views Data Mining» more  ICDM 2010»
14 years 8 months ago
Polishing the Right Apple: Anytime Classification Also Benefits Data Streams with Constant Arrival Times
Classification of items taken from data streams requires algorithms that operate in time sensitive and computationally constrained environments. Often, the available time for class...
Jin Shieh, Eamonn J. Keogh
SAC
2009
ACM
15 years 5 months ago
Evaluating algorithms that learn from data streams
In the past years, the theory and practice of machine learning and data mining have been focused on static and finite data sets from where learning algorithms generate a static m...
João Gama, Pedro Pereira Rodrigues, Raquel ...