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» Mining data streams: a review
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IPM
2006
151views more  IPM 2006»
13 years 8 months ago
Document clustering using nonnegative matrix factorization
A methodology for automatically identifying and clustering semantic features or topics in a heterogeneous text collection is presented. Textual data is encoded using a low rank no...
Farial Shahnaz, Michael W. Berry, V. Paul Pauca, R...
ICMCS
2009
IEEE
147views Multimedia» more  ICMCS 2009»
13 years 6 months ago
Knowledge discovery over community-sharing media: From signal to intelligence
The explosive growth of photos/videos and the advent of mediasharing services have drastically increased the volume of usercontributed multimedia resources, which bring profound s...
Winston H. Hsu, Tao Mei, Rong Yan
DATAMINE
2008
137views more  DATAMINE 2008»
13 years 9 months ago
Two heads better than one: pattern discovery in time-evolving multi-aspect data
Abstract. Data stream values are often associated with multiple aspects. For example, each value observed at a given time-stamp from environmental sensors may have an associated ty...
Jimeng Sun, Charalampos E. Tsourakakis, Evan Hoke,...
SDM
2009
SIAM
191views Data Mining» more  SDM 2009»
14 years 6 months ago
Adaptive Concept Drift Detection.
An established method to detect concept drift in data streams is to perform statistical hypothesis testing on the multivariate data in the stream. Statistical decision theory off...
Anton Dries, Ulrich Rückert
KDD
1995
ACM
108views Data Mining» more  KDD 1995»
14 years 10 days ago
A Statistical Perspective On Knowledge Discovery In Databases
The quest to nd models usefully characterizing data is a process central to the scienti c method, and has been carried out on many fronts. Researchers from an expanding number of ...
John F. Elder IV, Daryl Pregibon