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» Learning Bayesian Networks from Incomplete Databases
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118
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KDD
2004
ACM
124views Data Mining» more  KDD 2004»
16 years 1 months ago
Eigenspace-based anomaly detection in computer systems
We report on an automated runtime anomaly detection method at the application layer of multi-node computer systems. Although several network management systems are available in th...
Hisashi Kashima, Tsuyoshi Idé
218
Voted
ICDE
2008
IEEE
137views Database» more  ICDE 2008»
16 years 2 months ago
Stop Chasing Trends: Discovering High Order Models in Evolving Data
Abstract-- Many applications are driven by evolving data -patterns in web traffic, program execution traces, network event logs, etc., are often non-stationary. Building prediction...
Shixi Chen, Haixun Wang, Shuigeng Zhou, Philip S. ...
HPCN
1998
Springer
15 years 5 months ago
PARAFLOW: A Dataflow Distributed Data-Computing System
We describe the Paraflow system for connecting heterogeneous computing services together into a flexible and efficient data-mining metacomputer. There are three levels of parallel...
Roy Williams, Bruce Sears
ISMB
1994
15 years 2 months ago
Stochastic Motif Extraction Using Hidden Markov Model
In this paper, westudy the application of an ttMM(hidden Markov model) to the problem of representing protein sequencesby a stochastic motif. Astochastic protein motif represents ...
Yukiko Fujiwara, Minoru Asogawa, Akihiko Konagaya
GECCO
2003
Springer
160views Optimization» more  GECCO 2003»
15 years 6 months ago
Using Genetic Algorithms for Data Mining Optimization in an Educational Web-Based System
This paper presents an approach for classifying students in order to predict their final grade based on features extracted from logged data in an education web-based system. A comb...
Behrouz Minaei-Bidgoli, William F. Punch