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EPIA
2003
Springer
15 years 12 months ago
Mining Low Dimensionality Data Streams of Continuous Attributes
This paper presents an incremental and scalable learning algorithm in order to mine numeric, low dimensionality, high–cardinality, time–changing data streams. Within the Superv...
Francisco J. Ferrer-Troyano, Jesús S. Aguil...
KDD
2003
ACM
194views Data Mining» more  KDD 2003»
16 years 7 months ago
Finding recent frequent itemsets adaptively over online data streams
A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Consequently, the knowledge embedded in a data stream is more likely to be c...
Joong Hyuk Chang, Won Suk Lee
ICDM
2005
IEEE
189views Data Mining» more  ICDM 2005»
16 years 11 days ago
Integrating Hidden Markov Models and Spectral Analysis for Sensory Time Series Clustering
We present a novel approach for clustering sequences of multi-dimensional trajectory data obtained from a sensor network. The sensory time-series data present new challenges to da...
Jie Yin, Qiang Yang
FSS
2008
105views more  FSS 2008»
15 years 6 months ago
Mining multiple-level fuzzy blocks from multidimensional data
Multidimensional databases are now recognized as being the standard way to store aggregated and historized data. Multidimensional databases are designed to store information on me...
Yeow Wei Choong, Anne Laurent, Dominique Laurent
FGCS
2007
99views more  FGCS 2007»
15 years 6 months ago
Mining performance data for metascheduling decision support in the Grid
: Metaschedulers in the Grid needs dynamic information to support their scheduling decisions. Job response time on computing resources, for instance, is such a performance metric. ...
Hui Li, David L. Groep, Lex Wolters