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ICDT
2001
ACM
124views Database» more  ICDT 2001»
15 years 11 months ago
Why and Where: A Characterization of Data Provenance
Withthe proliferation of database views and curated databases, the issue of data provenance where a piece of data came from and the process by which it arrived in the database is b...
Peter Buneman, Sanjeev Khanna, Wang Chiew Tan
ICNSC
2007
IEEE
16 years 27 days ago
Combined Support Vector Novelty Detection for Multi-channel Combustion Data
— Multi-channel combustion data, consisting of gas pressure and two combustion chamber luminosity measurements, are investigated in the prediction of combustion instability. Wave...
Lei A. Clifton, Hujun Yin, David A. Clifton, Yang ...
INCDM
2010
Springer
208views Data Mining» more  INCDM 2010»
15 years 8 months ago
Combining Unsupervised and Supervised Data Mining Techniques for Conducting Customer Portfolio Analysis
Abstract. Leveraging the power of increasing amounts of data to analyze customer base for attracting and retaining the most valuable customers is a major problem facing companies i...
Zhiyuan Yao, Annika H. Holmbom, Tomas Eklund, Barb...
ACSW
2004
15 years 8 months ago
Early Assessment of Classification Performance
The ability to distinguish between objects is the fundamental to learning and intelligent behavior in general. The difference between two things is the information we seek; the pr...
Bostjan Brumen, Izidor Golob, Hannu Jaakkola, Tatj...
GEOS
2009
Springer
15 years 11 months ago
Bottom-Up Gazetteers: Learning from the Implicit Semantics of Geotags
As directories of named places, gazetteers link the names to geographic footprints and place types. Most existing gazetteers are managed strictly top-down: entries can only be adde...
Carsten Keßler, Patrick Maué, Jan Tor...