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ICDM
2010
IEEE
115views Data Mining» more  ICDM 2010»
15 years 2 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
KDD
2005
ACM
80views Data Mining» more  KDD 2005»
16 years 4 months ago
Wavelet synopsis for data streams: minimizing non-euclidean error
We consider the wavelet synopsis construction problem for data streams where given n numbers we wish to estimate the data by constructing a synopsis, whose size, say B is much sma...
Sudipto Guha, Boulos Harb
ISCI
1998
139views more  ISCI 1998»
15 years 4 months ago
A Rough Set Approach to Attribute Generalization in Data Mining
This paper presents a method for updating approximations of a concept incrementally. The results can be used to implement a quasi-incremental algorithm for learning classification...
Chien-Chung Chan
KDD
2009
ACM
217views Data Mining» more  KDD 2009»
16 years 5 months ago
Efficient anomaly monitoring over moving object trajectory streams
Lately there exist increasing demands for online abnormality monitoring over trajectory streams, which are obtained from moving object tracking devices. This problem is challengin...
Yingyi Bu, Lei Chen 0002, Ada Wai-Chee Fu, Dawei L...
CLIMA
2004
15 years 5 months ago
The Apriori Stochastic Dependency Detection (ASDD) Algorithm for Learning Stochastic Logic Rules
Apriori Stochastic Dependency Detection (ASDD) is an algorithm for fast induction of stochastic logic rules from a database of observations made by an agent situated in an environm...
Christopher Child, Kostas Stathis