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KDD
2008
ACM
174views Data Mining» more  KDD 2008»
14 years 9 months ago
Automatic identification of quasi-experimental designs for discovering causal knowledge
Researchers in the social and behavioral sciences routinely rely on quasi-experimental designs to discover knowledge from large databases. Quasi-experimental designs (QEDs) exploi...
David D. Jensen, Andrew S. Fast, Brian J. Taylor, ...
KDD
2006
ACM
222views Data Mining» more  KDD 2006»
14 years 9 months ago
A component-based framework for knowledge discovery in bioinformatics
Motivation: In the field of bioinformatics there is an emerging need to integrate all knowledge discovery steps into a standardized modular framework. Indeed, component-based deve...
Julien Etienne, Bernd Wachmann, Lei Zhang
KDD
2003
ACM
130views Data Mining» more  KDD 2003»
14 years 9 months ago
Towards systematic design of distance functions for data mining applications
Distance function computation is a key subtask in many data mining algorithms and applications. The most effective form of the distance function can only be expressed in the conte...
Charu C. Aggarwal
KDD
2003
ACM
180views Data Mining» more  KDD 2003»
14 years 9 months ago
Classifying large data sets using SVMs with hierarchical clusters
Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...
Hwanjo Yu, Jiong Yang, Jiawei Han
KDD
2002
ACM
155views Data Mining» more  KDD 2002»
14 years 9 months ago
SyMP: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets
We propose a new clustering algorithm, called SyMP, which is based on synchronization of pulse-coupled oscillators. SyMP represents each data point by an Integrate-and-Fire oscill...
Hichem Frigui
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