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» On Appropriate Assumptions to Mine Data Streams: Analysis an...
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ICDM
2007
IEEE
158views Data Mining» more  ICDM 2007»
13 years 11 months ago
On Appropriate Assumptions to Mine Data Streams: Analysis and Practice
Recent years have witnessed an increasing number of studies in stream mining, which aim at building an accurate model for continuously arriving data. Somehow most existing work ma...
Jing Gao, Wei Fan, Jiawei Han
KDD
2004
ACM
117views Data Mining» more  KDD 2004»
14 years 5 months ago
Systematic data selection to mine concept-drifting data streams
One major problem of existing methods to mine data streams is that it makes ad hoc choices to combine most recent data with some amount of old data to search the new hypothesis. T...
Wei Fan
DAWAK
2010
Springer
13 years 6 months ago
Mining Closed Itemsets in Data Stream Using Formal Concept Analysis
Mining of frequent closed itemsets has been shown to be more efficient than mining frequent itemsets for generating non-redundant association rules. The task is challenging in data...
Anamika Gupta, Vasudha Bhatnagar, Naveen Kumar
DASFAA
2010
IEEE
225views Database» more  DASFAA 2010»
13 years 5 months ago
Mining Regular Patterns in Data Streams
Discovering interesting patterns from high-speed data streams is a challenging problem in data mining. Recently, the support metric-based frequent pattern mining from data stream h...
Syed Khairuzzaman Tanbeer, Chowdhury Farhan Ahmed,...
ICDM
2009
IEEE
141views Data Mining» more  ICDM 2009»
13 years 11 months ago
Discovering Excitatory Networks from Discrete Event Streams with Applications to Neuronal Spike Train Analysis
—Mining temporal network models from discrete event streams is an important problem with applications in computational neuroscience, physical plant diagnostics, and human-compute...
Debprakash Patnaik, Srivatsan Laxman, Naren Ramakr...