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KDD
2010
ACM
253views Data Mining» more  KDD 2010»
15 years 1 months ago
Mining periodic behaviors for moving objects
Periodicity is a frequently happening phenomenon for moving objects. Finding periodic behaviors is essential to understanding object movements. However, periodic behaviors could b...
Zhenhui Li, Bolin Ding, Jiawei Han, Roland Kays, P...
SIGSOFT
2007
ACM
15 years 10 months ago
Training on errors experiment to detect fault-prone software modules by spam filter
The fault-prone module detection in source code is of importance for assurance of software quality. Most of previous fault-prone detection approaches are based on software metrics...
Osamu Mizuno, Tohru Kikuno
KDD
2008
ACM
148views Data Mining» more  KDD 2008»
15 years 10 months ago
Get another label? improving data quality and data mining using multiple, noisy labelers
This paper addresses the repeated acquisition of labels for data items when the labeling is imperfect. We examine the improvement (or lack thereof) in data quality via repeated la...
Victor S. Sheng, Foster J. Provost, Panagiotis G. ...
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
15 years 10 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
SIGMOD
2008
ACM
138views Database» more  SIGMOD 2008»
15 years 9 months ago
Sampling time-based sliding windows in bounded space
Random sampling is an appealing approach to build synopses of large data streams because random samples can be used for a broad spectrum of analytical tasks. Users are often inter...
Rainer Gemulla, Wolfgang Lehner