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ESANN
2004
13 years 10 months ago
Neural networks for data mining: constrains and open problems
When we talk about using neural networks for data mining we have in mind the original data mining scope and challenge. How did neural networks meet this challenge? Can we run neura...
Razvan Andonie, Boris Kovalerchuk
IADIS
2003
13 years 10 months ago
Informatization and E-Business Model Application for Distributed Data Mining Using Mobile Agents
Distributed data mining (DDM) is the semi-automatic pattern extraction of distributed data sources. The next generation of the data mining studies will be distributed data mining ...
Ezendu Ifeanyi Ariwa, Mohamed B. Senousy, Mohamed ...
KDD
2006
ACM
118views Data Mining» more  KDD 2006»
14 years 9 months ago
Maximum profit mining and its application in software development
While most software defects (i.e., bugs) are corrected and tested as part of the lengthy software development cycle, enterprise software vendors often have to release software pro...
Charles X. Ling, Victor S. Sheng, Tilmann F. W. Br...
KDD
2000
ACM
129views Data Mining» more  KDD 2000»
14 years 8 days ago
Evolutionary algorithms in data mining: multi-objective performance modeling for direct marketing
Predictive models in direct marketing seek to identify individuals most likely to respond to promotional solicitations or other intervention programs. While standard modeling appr...
Siddhartha Bhattacharyya
VLDB
2005
ACM
140views Database» more  VLDB 2005»
14 years 2 months ago
Loadstar: Load Shedding in Data Stream Mining
In this demo, we show that intelligent load shedding is essential in achieving optimum results in mining data streams under various resource constraints. The Loadstar system intro...
Yun Chi, Haixun Wang, Philip S. Yu