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» Intrusion Detection Based on Data Mining
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131
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JDWM
2006
84views more  JDWM 2006»
15 years 3 months ago
Discovering Surprising Instances of Simpson's Paradox in Hierarchical Multidimensional Data
This paper focuses on the discovery of surprising, unexpected patterns, based on a data mining method that consists of detecting instances of Simpson's paradox. By its very n...
Carem C. Fabris, Alex Alves Freitas
138
Voted
APCCM
2006
15 years 5 months ago
Network data mining: methods and techniques for discovering deep linkage between attributes
Network Data Mining identifies emergent networks between myriads of individual data items and utilises special algorithms that aid visualisation of `emergent' patterns and tre...
John Galloway, Simeon J. Simoff
130
Voted
ICDM
2009
IEEE
198views Data Mining» more  ICDM 2009»
15 years 10 months ago
Information Extraction for Clinical Data Mining: A Mammography Case Study
Abstract—Breast cancer is the leading cause of cancer mortality in women between the ages of 15 and 54. During mammography screening, radiologists use a strict lexicon (BI-RADS) ...
Houssam Nassif, Ryan Woods, Elizabeth S. Burnside,...
KDD
2000
ACM
211views Data Mining» more  KDD 2000»
15 years 7 months 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
KDD
2010
ACM
300views Data Mining» more  KDD 2010»
15 years 7 months ago
Mining top-k frequent items in a data stream with flexible sliding windows
We study the problem of finding the k most frequent items in a stream of items for the recently proposed max-frequency measure. Based on the properties of an item, the maxfrequen...
Hoang Thanh Lam, Toon Calders