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» Mining Multiple Large Databases
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IJCNN
2008
IEEE
15 years 8 months ago
Two-level clustering approach to training data instance selection: A case study for the steel industry
— Nowadays, huge amounts of information from different industrial processes are stored into databases and companies can improve their production efficiency by mining some new kn...
Heli Koskimäki, Ilmari Juutilainen, Perttu La...
110
Voted
KDD
2004
ACM
147views Data Mining» more  KDD 2004»
15 years 7 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
116
Voted
PKDD
1999
Springer
106views Data Mining» more  PKDD 1999»
15 years 6 months ago
Heuristic Measures of Interestingness
When mining a large database, the number of patterns discovered can easily exceed the capabilities of a human user to identify interesting results. To address this problem, variou...
Robert J. Hilderman, Howard J. Hamilton
KDD
2010
ACM
224views Data Mining» more  KDD 2010»
15 years 5 months ago
Ensemble pruning via individual contribution ordering
An ensemble is a set of learned models that make decisions collectively. Although an ensemble is usually more accurate than a single learner, existing ensemble methods often tend ...
Zhenyu Lu, Xindong Wu, Xingquan Zhu, Josh Bongard
KDD
2010
ACM
323views Data Mining» more  KDD 2010»
15 years 3 months ago
TIARA: a visual exploratory text analytic system
In this paper, we present a novel exploratory visual analytic system called TIARA (Text Insight via Automated Responsive Analytics), which combines text analytics and interactive ...
Furu Wei, Shixia Liu, Yangqiu Song, Shimei Pan, Mi...