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GFKL
2005
Springer
133views Data Mining» more  GFKL 2005»
14 years 2 months ago
Finding Persisting States for Knowledge Discovery in Time Series
Abstract. Knowledge Discovery in time series usually requires symbolic time series. Many discretization methods that convert numeric time series to symbolic time series ignore the ...
Fabian Mörchen, Alfred Ultsch
SDM
2008
SIAM
122views Data Mining» more  SDM 2008»
13 years 10 months ago
Type-Independent Correction of Sample Selection Bias via Structural Discovery and Re-balancing
Sample selection bias is a common problem in many real world applications, where training data are obtained under realistic constraints that make them follow a different distribut...
Jiangtao Ren, Xiaoxiao Shi, Wei Fan, Philip S. Yu
ACSAC
2001
IEEE
14 years 19 days ago
Mining Alarm Clusters to Improve Alarm Handling Efficiency
It is a well-known problem that intrusion detection systems overload their human operators by triggering thousands of alarms per day. As a matter of fact, we have been asked by on...
Klaus Julisch
ICDM
2009
IEEE
109views Data Mining» more  ICDM 2009»
14 years 3 months ago
Knowledge Discovery from Citation Networks
—Knowledge discovery from scientific articles has received increasing attentions recently since huge repositories are made available by the development of the Internet and digit...
Zhen Guo, Zhongfei Zhang, Shenghuo Zhu, Yun Chi, Y...
KDD
1998
ACM
122views Data Mining» more  KDD 1998»
14 years 1 months ago
Memory Placement Techniques for Parallel Association Mining
Many data mining tasks (e.g., Association Rules, Sequential Patterns) use complex pointer-based data structures (e.g., hash trees) that typically suffer from sub-optimal data loca...
Srinivasan Parthasarathy, Mohammed Javeed Zaki, We...