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ICDM
2006
IEEE
137views Data Mining» more  ICDM 2006»
15 years 3 months ago
Mining Complex Time-Series Data by Learning Markovian Models
In this paper, we propose a novel and general approach for time-series data mining. As an alternative to traditional ways of designing specific algorithm to mine certain kind of ...
Yi Wang, Lizhu Zhou, Jianhua Feng, Jianyong Wang, ...
KDD
2004
ACM
124views Data Mining» more  KDD 2004»
15 years 10 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
ISPA
2004
Springer
15 years 3 months ago
Cayley DHTs - A Group-Theoretic Framework for Analyzing DHTs Based on Cayley Graphs
Static DHT topologies influence important features of such DHTs such as scalability, communication load balancing, routing efficiency and fault tolerance. Nevertheless, it is co...
Changtao Qu, Wolfgang Nejdl, Matthias Kriesell
AUSDM
2007
Springer
193views Data Mining» more  AUSDM 2007»
15 years 3 months ago
Are Zero-suppressed Binary Decision Diagrams Good for Mining Frequent Patterns in High Dimensional Datasets?
Mining frequent patterns such as frequent itemsets is a core operation in many important data mining tasks, such as in association rule mining. Mining frequent itemsets in high-di...
Elsa Loekito, James Bailey
ISI
2008
Springer
14 years 9 months ago
Data mining for social network analysis
A social network is defined as a social structure of individuals, who are related (directly or indirectly to each other) based on a common relation of interest, e.g. friendship, t...
J. Srivastava