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PPOPP
2005
ACM
13 years 10 months ago
A sampling-based framework for parallel data mining
The goal of data mining algorithm is to discover useful information embedded in large databases. Frequent itemset mining and sequential pattern mining are two important data minin...
Shengnan Cong, Jiawei Han, Jay Hoeflinger, David A...
PKDD
2004
Springer
135views Data Mining» more  PKDD 2004»
13 years 10 months ago
A Unified and Flexible Framework for Comparing Simple and Complex Patterns
One of the most important operations involving Data Mining patterns is computing their similarity. In this paper we present a general framework for comparing both simple and comple...
Ilaria Bartolini, Paolo Ciaccia, Irene Ntoutsi, Ma...
KDD
2004
ACM
151views Data Mining» more  KDD 2004»
14 years 5 months ago
Feature selection in scientific applications
Numerous applications of data mining to scientific data involve the induction of a classification model. In many cases, the collection of data is not performed with this task in m...
Erick Cantú-Paz, Shawn Newsam, Chandrika Ka...
KDD
2006
ACM
222views Data Mining» more  KDD 2006»
14 years 5 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
PAKDD
2007
ACM
166views Data Mining» more  PAKDD 2007»
13 years 11 months ago
gPrune: A Constraint Pushing Framework for Graph Pattern Mining
In graph mining applications, there has been an increasingly strong urge for imposing user-specified constraints on the mining results. However, unlike most traditional itemset co...
Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu