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» Specification Mining with Few False Positives
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79
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TACAS
2009
Springer
95views Algorithms» more  TACAS 2009»
15 years 8 months ago
Specification Mining with Few False Positives
Claire Le Goues, Westley Weimer
126
Voted
KDD
2005
ACM
161views Data Mining» more  KDD 2005»
16 years 1 months ago
Combining email models for false positive reduction
Machine learning and data mining can be effectively used to model, classify and discover interesting information for a wide variety of data including email. The Email Mining Toolk...
Shlomo Hershkop, Salvatore J. Stolfo
80
Voted
ICDM
2006
IEEE
89views Data Mining» more  ICDM 2006»
15 years 7 months ago
Plagiarism Detection in arXiv
We describe a large-scale application of methods for finding plagiarism and self-plagiarism in research document collections. The methods are applied to a collection of 284,834 d...
Daria Sorokina, Johannes Gehrke, Simeon Warner, Pa...
107
Voted
ESWA
2006
161views more  ESWA 2006»
15 years 1 months ago
Automated trend analysis of proteomics data using an intelligent data mining architecture
Proteomics is a field dedicated to the analysis and identification of proteins within an organism. Within proteomics, two-dimensional electrophoresis (2-DE) is currently unrivalle...
James Malone, Kenneth McGarry, Chris Bowerman
106
Voted
CIDM
2007
IEEE
15 years 1 months ago
Detection of Unknown Computer Worms Activity Based on Computer Behavior using Data Mining
— Detecting unknown worms is a challenging task. Extant solutions, such as anti-virus tools, rely mainly on prior explicit knowledge of specific worm signatures. As a result, aft...
Robert Moskovitch, Ido Gus, Shay Pluderman, Dima S...