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» Phenomenal Data Mining: From Data to Phenomena
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KDD
2000
ACM
211views Data Mining» more  KDD 2000»
14 years 26 days ago
Mining IC test data to optimize VLSI testing
We describe an application of data mining and decision analysis to the problem of die-level functional test in integrated circuit manufacturing. Integrated circuits are fabricated...
Tony Fountain, Thomas G. Dietterich, Bill Sudyka
JIIS
2006
113views more  JIIS 2006»
13 years 9 months ago
Spatial ordering and encoding for geographic data mining and visualization
: Geographic information (e.g., locations, networks, and nearest neighbors) are unique and different from other aspatial attributes (e.g., population, sales, or income). It is a ch...
Diansheng Guo, Mark Gahegan
KDD
2003
ACM
130views Data Mining» more  KDD 2003»
14 years 9 months ago
Towards systematic design of distance functions for data mining applications
Distance function computation is a key subtask in many data mining algorithms and applications. The most effective form of the distance function can only be expressed in the conte...
Charu C. Aggarwal
LSSC
2001
Springer
14 years 1 months ago
On the Parallelization of the Sparse Grid Approach for Data Mining
Abstract. Recently we presented a new approach [5, 6] to the classification problem arising in data mining. It is based on the regularization network approach, but in contrast to ...
Jochen Garcke, Michael Griebel
KDD
2001
ACM
253views Data Mining» more  KDD 2001»
14 years 9 months ago
GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
Jens-Peter Dittrich, Bernhard Seeger