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» Exploiting Temporal Relations in Mining Hepatitis Data
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ICDM
2005
IEEE
137views Data Mining» more  ICDM 2005»
14 years 1 months ago
Leveraging Relational Autocorrelation with Latent Group Models
The presence of autocorrelation provides a strong motivation for using relational learning and inference techniques. Autocorrelation is a statistical dependence between the values...
Jennifer Neville, David Jensen
KDD
1998
ACM
164views Data Mining» more  KDD 1998»
13 years 12 months ago
A Data Mining Support Environment and its Application on Insurance Data
Huge masses of digital data about products, customers and competitors have become available for companies in the services sector. In order to exploit its inherent (and often hidde...
Martin Staudt, Jörg-Uwe Kietz, Ulrich Reimer
ICDE
1993
IEEE
158views Database» more  ICDE 1993»
13 years 11 months ago
Unification of Temporal Data Models
To add time su port to the relational model, both first normal form (fNF and non-INF appmches have maining within 1NF when time support is added may introduce data redundancy. The...
Christian S. Jensen, Michael D. Soo, Richard T. Sn...
KDD
2007
ACM
209views Data Mining» more  KDD 2007»
14 years 8 months ago
Temporal causal modeling with graphical granger methods
The need for mining causality, beyond mere statistical correlations, for real world problems has been recognized widely. Many of these applications naturally involve temporal data...
Andrew Arnold, Yan Liu, Naoki Abe
ECAI
2004
Springer
14 years 1 months ago
Exploiting Association and Correlation Rules - Parameters for Improving the K2 Algorithm
A Bayesian network is an appropriate tool to deal with the uncertainty that is typical of real-life applications. Bayesian network arcs represent statistical dependence between dif...
Evelina Lamma, Fabrizio Riguzzi, Sergio Storari