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AUSDM
2006
Springer
100views Data Mining» more  AUSDM 2006»
15 years 10 months ago
Data Mining Methodological Weaknesses and Suggested Fixes
Predictive accuracy claims should give explicit descriptions of the steps followed, with access to the code used. This allows referees and readers to check for common traps, and t...
John H. Maindonald
KDD
1995
ACM
129views Data Mining» more  KDD 1995»
15 years 10 months ago
Feature Extraction for Massive Data Mining
Techniques for learning from data typically require data to be in standard form. Measurements must be encoded in a numerical format such as binary true-or-false features, numerica...
V. Seshadri, Raguram Sasisekharan, Sholom M. Weiss
FGCS
2007
106views more  FGCS 2007»
15 years 6 months ago
Distributed data mining services leveraging WSRF
The continuous increase of data volumes available from many sources raises new challenges for their effective understanding. Knowledge discovery in large data repositories involv...
Antonio Congiusta, Domenico Talia, Paolo Trunfio
GIS
2008
ACM
16 years 7 months ago
GEDMWA: geospatial exploratory data mining web agent
An abundance of geospatial information is flourishing on the Internet but mining and disseminating these data is a daunting task. With anything published on the web available to t...
Edward Pultar, Martin Raubal, Michael F. Goodchild
HICSS
2005
IEEE
124views Biometrics» more  HICSS 2005»
16 years 5 days ago
Information Policy, Data Mining, and National Security: False Positives and Unidentified Negatives
Since 9/11, intelligence agencies in the United States have expanded experimentation and use of data mining and analysis techniques to combat terrorism. These efforts have generat...
Terrence A. Maxwell