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» Mining data streams: a review
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SDM
2007
SIAM
187views Data Mining» more  SDM 2007»
13 years 10 months ago
Topic Models over Text Streams: A Study of Batch and Online Unsupervised Learning
Topic modeling techniques have widespread use in text data mining applications. Some applications use batch models, which perform clustering on the document collection in aggregat...
Arindam Banerjee, Sugato Basu
CIKM
2010
Springer
13 years 7 months ago
Partial drift detection using a rule induction framework
The major challenge in mining data streams is the issue of concept drift, the tendency of the underlying data generation process to change over time. In this paper, we propose a g...
Damon Sotoudeh, Aijun An
AUSDM
2007
Springer
100views Data Mining» more  AUSDM 2007»
14 years 3 months ago
Determining Termhood for Learning Domain Ontologies using Domain Prevalence and Tendency
In the course of reviewing existing automatic term recognition techniques for applications in ontology learning, we came across four issues which can be improved upon. We proposed...
Wilson Wong, Wei Liu, Mohammed Bennamoun
ICDE
2002
IEEE
204views Database» more  ICDE 2002»
14 years 10 months ago
Approximating a Data Stream for Querying and Estimation: Algorithms and Performance Evaluation
Obtaining fast and good quality approximations to data distributions is a problem of central interest to database management. A variety of popular database applications including,...
Sudipto Guha, Nick Koudas
KDD
2007
ACM
184views Data Mining» more  KDD 2007»
14 years 9 months ago
GraphScope: parameter-free mining of large time-evolving graphs
How can we find communities in dynamic networks of social interactions, such as who calls whom, who emails whom, or who sells to whom? How can we spot discontinuity timepoints in ...
Jimeng Sun, Christos Faloutsos, Spiros Papadimitri...