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» Hybrid Learning Scheme for Data Mining Applications
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KDD
2007
ACM
152views Data Mining» more  KDD 2007»
14 years 8 months ago
Relational data pre-processing techniques for improved securities fraud detection
Commercial datasets are often large, relational, and dynamic. They contain many records of people, places, things, events and their interactions over time. Such datasets are rarel...
Andrew Fast, Lisa Friedland, Marc Maier, Brian Tay...
TNN
1998
121views more  TNN 1998»
13 years 7 months ago
Detection of mines and minelike targets using principal component and neural-network methods
— This paper introduces a new system for real-time detection and classification of arbitrarily scattered surface-laid mines from multispectral imagery data of a minefield. The ...
Xi Miao, Mahmood R. Azimi-Sadjadi, Bin Tan, A. C. ...
KDD
2004
ACM
187views Data Mining» more  KDD 2004»
14 years 8 months ago
IMMC: incremental maximum margin criterion
Subspace learning approaches have attracted much attention in academia recently. However, the classical batch algorithms no longer satisfy the applications on streaming data or la...
Jun Yan, Benyu Zhang, Shuicheng Yan, Qiang Yang, H...
SIGCSE
2006
ACM
163views Education» more  SIGCSE 2006»
14 years 1 months ago
TextMOLE: text mining operations library and environment
The paper describes the first version of the TextMOLE (Text Mining Operations Library and Environment) system for textual data mining. Currently TextMOLE acts as an advanced inde...
Daniel B. Waegel, April Kontostathis
ICDM
2005
IEEE
190views Data Mining» more  ICDM 2005»
14 years 1 months ago
Adaptive Clustering: Obtaining Better Clusters Using Feedback and Past Experience
Adaptive clustering uses external feedback to improve cluster quality; past experience serves to speed up execution time. An adaptive clustering environment is proposed that uses ...
Abraham Bagherjeiran, Christoph F. Eick, Chun-Shen...