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» Discovering Classification from Data of Multiple Sources
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IEAAIE
2009
Springer
15 years 8 months ago
Incremental Mining of Ontological Association Rules in Evolving Environments
The process of knowledge discovery from databases is a knowledge intensive, highly user-oriented practice, thus has recently heralded the development of ontology-incorporated data ...
Ming-Cheng Tseng, Wen-Yang Lin
CINQ
2004
Springer
157views Database» more  CINQ 2004»
15 years 5 months ago
Inductive Databases and Multiple Uses of Frequent Itemsets: The cInQ Approach
Inductive databases (IDBs) have been proposed to afford the problem of knowledge discovery from huge databases. With an IDB the user/analyst performs a set of very different operat...
Jean-François Boulicaut
ISD
1999
Springer
213views Database» more  ISD 1999»
15 years 6 months ago
A Probabilistic Approach to Environmental Change Detection with Area-Class Map Data
One of the primary methods of studying change in the natural and man-made environment is that of comparison of multi-date maps and images of the earth's surface. Such comparis...
Christopher B. Jones, J. Mark Ware, David R. Mille...
ICDE
2006
IEEE
124views Database» more  ICDE 2006»
15 years 7 months ago
Systematic Approach for Optimizing Complex Mining Tasks on Multiple Databases
It has been well recognized that data mining is an interactive and iterative process. In order to support this process, one of the long-term goals of data mining research has been...
Ruoming Jin, Gagan Agrawal
CVPR
2007
IEEE
16 years 3 months ago
Learning Color Names from Real-World Images
Within a computer vision context color naming is the action of assigning linguistic color labels to image pixels. In general, research on color naming applies the following paradi...
Joost van de Weijer, Cordelia Schmid, Jakob J. Ver...