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» Mining time-changing data streams
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ICDM
2005
IEEE
217views Data Mining» more  ICDM 2005»
14 years 1 months ago
Improving Automatic Query Classification via Semi-Supervised Learning
Accurate topical classification of user queries allows for increased effectiveness and efficiency in general-purpose web search systems. Such classification becomes critical if th...
Steven M. Beitzel, Eric C. Jensen, Ophir Frieder, ...
AINA
2008
IEEE
13 years 9 months ago
A Communication-Efficient Distributed Clustering Algorithm for Sensor Networks
Sensor networks usually generate continuous stream of data over time. Clustering sensor data as a core task of mining sensor data plays an essential role in analytical application...
Amirhosein Taherkordi, Reza Mohammadi, Frank Elias...
DATAMINE
2008
137views more  DATAMINE 2008»
13 years 7 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 4 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
2008
ACM
186views Data Mining» more  KDD 2008»
14 years 8 months ago
Scalable and near real-time burst detection from eCommerce queries
In large scale online systems like Search, eCommerce, or social network applications, user queries represent an important dimension of activities that can be used to study the imp...
Nish Parikh, Neel Sundaresan