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KDD
2007
ACM
178views Data Mining» more  KDD 2007»
16 years 6 months ago
Practical learning from one-sided feedback
In many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. Such applications include spam filt...
D. Sculley
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
16 years 6 months ago
A fast algorithm for finding frequent episodes in event streams
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
KDD
2006
ACM
130views Data Mining» more  KDD 2006»
16 years 6 months ago
Efficient anonymity-preserving data collection
The output of a data mining algorithm is only as good as its inputs, and individuals are often unwilling to provide accurate data about sensitive topics such as medical history an...
Justin Brickell, Vitaly Shmatikov
KDD
2006
ACM
272views Data Mining» more  KDD 2006»
16 years 6 months ago
YALE: rapid prototyping for complex data mining tasks
KDD is a complex and demanding task. While a large number of methods has been established for numerous problems, many challenges remain to be solved. New tasks emerge requiring th...
Ingo Mierswa, Michael Wurst, Ralf Klinkenberg, Mar...
167
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KDD
2005
ACM
170views Data Mining» more  KDD 2005»
16 years 6 months ago
Parallel mining of closed sequential patterns
Discovery of sequential patterns is an essential data mining task with broad applications. Among several variations of sequential patterns, closed sequential pattern is the most u...
Shengnan Cong, Jiawei Han, David A. Padua
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