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» Algorithms for time series knowledge mining
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DASFAA
2005
IEEE
157views Database» more  DASFAA 2005»
13 years 12 months ago
Adaptively Detecting Aggregation Bursts in Data Streams
Finding bursts in data streams is attracting much attention in research community due to its broad applications. Existing burst detection methods suffer the problems that 1) the p...
Aoying Zhou, Shouke Qin, Weining Qian
ICSE
2012
IEEE-ACM
11 years 8 months ago
WhoseFault: Automatic developer-to-fault assignment through fault localization
—This paper describes a new technique, which automatically selects the most appropriate developers for fixing the fault represented by a failing test case, and provides a diagno...
Francisco Servant, James A. Jones
KDD
2010
ACM
272views Data Mining» more  KDD 2010»
13 years 10 months ago
Beyond heuristics: learning to classify vulnerabilities and predict exploits
The security demands on modern system administration are enormous and getting worse. Chief among these demands, administrators must monitor the continual ongoing disclosure of sof...
Mehran Bozorgi, Lawrence K. Saul, Stefan Savage, G...
DATAMINE
2002
147views more  DATAMINE 2002»
13 years 6 months ago
Discretization: An Enabling Technique
Discrete values have important roles in data mining and knowledge discovery. They are about intervals of numbers which are more concise to represent and specify, easier to use and ...
Huan Liu, Farhad Hussain, Chew Lim Tan, Manoranjan...
PKDD
2010
Springer
212views Data Mining» more  PKDD 2010»
13 years 4 months ago
Cross Validation Framework to Choose amongst Models and Datasets for Transfer Learning
Abstract. One solution to the lack of label problem is to exploit transfer learning, whereby one acquires knowledge from source-domains to improve the learning performance in the t...
ErHeng Zhong, Wei Fan, Qiang Yang, Olivier Versche...