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» A Fully Distributed Framework for Cost-Sensitive Data Mining
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KDD
2007
ACM
152views Data Mining» more  KDD 2007»
14 years 8 months ago
A framework for classification and segmentation of massive audio data streams
In recent years, the proliferation of VOIP data has created a number of applications in which it is desirable to perform quick online classification and recognition of massive voi...
Charu C. Aggarwal
JPDC
2008
134views more  JPDC 2008»
13 years 7 months ago
Middleware for data mining applications on clusters and grids
This paper gives an overview of two middleware systems that have been developed over the last 6 years to address the challenges involved in developing parallel and distributed imp...
Leonid Glimcher, Ruoming Jin, Gagan Agrawal
CORR
2010
Springer
194views Education» more  CORR 2010»
13 years 4 months ago
An Effective Method of Image Retrieval using Image Mining Techniques
The present research scholars are having keen interest in doing their research activities in the area of Data mining all over the world. Especially, [13]Mining Image data is the o...
A. Kannan, V. Mohan, N. Anbazhagan
TMM
2002
104views more  TMM 2002»
13 years 7 months ago
Spatial contextual classification and prediction models for mining geospatial data
Modeling spatial context (e.g., autocorrelation) is a key challenge in classification problems that arise in geospatial domains. Markov random fields (MRF) is a popular model for i...
Shashi Shekhar, Paul R. Schrater, Ranga Raju Vatsa...
CIKM
2010
Springer
13 years 6 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