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KDD
2009
ACM
224views Data Mining» more  KDD 2009»
15 years 6 months ago
Issues in evaluation of stream learning algorithms
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
João Gama, Raquel Sebastião, Pedro P...
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
16 years 2 months ago
Efficient methods for topic model inference on streaming document collections
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
Limin Yao, David M. Mimno, Andrew McCallum
KDD
2005
ACM
151views Data Mining» more  KDD 2005»
16 years 2 months ago
Discovering evolutionary theme patterns from text: an exploration of temporal text mining
Temporal Text Mining (TTM) is concerned with discovering temporal patterns in text information collected over time. Since most text information bears some time stamps, TTM has man...
Qiaozhu Mei, ChengXiang Zhai
SDM
2009
SIAM
208views Data Mining» more  SDM 2009»
15 years 11 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...
138
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DMSN
2006
ACM
15 years 7 months ago
Intelligent system monitoring on large clusters
Modern data centers have a large number of components that must be monitored, including servers, switches/routers, and environmental control systems. This paper describes InteMon,...
Jimeng Sun, Evan Hoke, John D. Strunk, Gregory R. ...