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» Hybrid Learning Scheme for Data Mining Applications
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KDD
2006
ACM
118views Data Mining» more  KDD 2006»
14 years 8 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...
GIS
2009
ACM
13 years 11 months ago
Dynamic network data exploration through semi-supervised functional embedding
The paper presents a framework for semi-supervised nonlinear embedding methods useful for exploratory analysis and visualization of spatio-temporal network data. The method provid...
Alexei Pozdnoukhov
ICDM
2009
IEEE
171views Data Mining» more  ICDM 2009»
13 years 5 months ago
Hybrid Clustering by Integrating Text and Citation Based Graphs in Journal Database Analysis
We propose a hybrid clustering strategy by integrating heterogeneous information sources as graphs. The hybrid clustering method is extended on the basis of modularity based Louva...
Xinhai Liu, Shi Yu, Yves Moreau, Frizo A. L. Janss...
KDD
2002
ACM
173views Data Mining» more  KDD 2002»
14 years 8 months ago
LumberJack: Intelligent Discovery and Analysis of Web User Traffic Composition
Web Usage Mining enables new understanding of user goals on the Web. This understanding has broad applications, and traditional mining techniques such as association rules have bee...
Ed Huai-hsin Chi, Adam Rosien, Jeffrey Heer
GCC
2007
Springer
14 years 1 months ago
Data Persistence in Structured P2P Networks with Redundancy Schemes
Data service is the principle application in structured P2P networks. And in many cases, we need the data to persist for a long time. So how to persist the data service and how lo...
Hongxing Li, Guihai Chen