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PAKDD
2007
ACM
115views Data Mining» more  PAKDD 2007»
14 years 1 months ago
Intelligent Sequential Mining Via Alignment: Optimization Techniques for Very Large DB
The shear volume of the results in traditional support based frequent sequential pattern mining methods has led to increasing interest in new intelligent mining methods to find mo...
Hye-Chung Kum, Joong Hyuk Chang, Wei Wang 0010
MLDM
2009
Springer
14 years 1 months ago
Relational Frequent Patterns Mining for Novelty Detection from Data Streams
We face the problem of novelty detection from stream data, that is, the identification of new or unknown situations in an ordered sequence of objects which arrive on-line, at cons...
Michelangelo Ceci, Annalisa Appice, Corrado Loglis...
HICSS
2003
IEEE
171views Biometrics» more  HICSS 2003»
14 years 20 days ago
Improving the Efficiency of Interactive Sequential Pattern Mining by Incremental Pattern Discovery
The discovery of sequential patterns, which extends beyond frequent item-set finding of association rule mining, has become a challenging task due to its complexity. Essentially, ...
Ming-Yen Lin, Suh-Yin Lee
ADMA
2006
Springer
121views Data Mining» more  ADMA 2006»
14 years 1 months ago
A New Polynomial Time Algorithm for Bayesian Network Structure Learning
We propose a new algorithm called SCD for learning the structure of a Bayesian network. The algorithm is a kind of constraintbased algorithm. By taking advantage of variable orderi...
Sanghack Lee, Jihoon Yang, Sungyong Park
SDM
2009
SIAM
343views Data Mining» more  SDM 2009»
14 years 4 months ago
Change-Point Detection in Time-Series Data by Direct Density-Ratio Estimation.
Change-point detection is the problem of discovering time points at which properties of time-series data change. This covers a broad range of real-world problems and has been acti...
Masashi Sugiyama, Yoshinobu Kawahara