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KDD
2004
ACM
147views Data Mining» more  KDD 2004»
14 years 2 months ago
Clustering time series from ARMA models with clipped data
Clustering time series is a problem that has applications in a wide variety of fields, and has recently attracted a large amount of research. In this paper we focus on clustering...
Anthony J. Bagnall, Gareth J. Janacek
SAC
2009
ACM
14 years 4 months ago
Combining statistics and semantics via ensemble model for document clustering
Incorporating background knowledge into data mining algorithms is an important but challenging problem. Current approaches in semi-supervised learning require explicit knowledge p...
Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan
KDD
2005
ACM
139views Data Mining» more  KDD 2005»
14 years 2 months ago
Learning to predict train wheel failures
This paper describes a successful but challenging application of data mining in the railway industry. The objective is to optimize maintenance and operation of trains through prog...
Chunsheng Yang, Sylvain Létourneau
ISDA
2009
IEEE
14 years 3 months ago
From Local Patterns to Global Models: Towards Domain Driven Educational Process Mining
Educational process mining (EPM) aims at (i) constructing complete and compact educational process models that are able to reproduce all observed behavior (process model discovery...
Nikola Trcka, Mykola Pechenizkiy
DAWAK
1999
Springer
14 years 1 months ago
Modeling KDD Processes within the Inductive Database Framework
One of the most challenging problems in data manipulation in the future is to be able to e ciently handle very large databases but also multiple induced properties or generalizatio...
Jean-François Boulicaut, Mika Klemettinen, ...