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» A Practical Algorithm to Find the Best Subsequence Patterns
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ICDM
2003
IEEE
141views Data Mining» more  ICDM 2003»
14 years 21 days ago
TSP: Mining Top-K Closed Sequential Patterns
Sequential pattern mining has been studied extensively in data mining community. Most previous studies require the specification of a minimum support threshold to perform the min...
Petre Tzvetkov, Xifeng Yan, Jiawei Han
KDD
2004
ACM
144views Data Mining» more  KDD 2004»
14 years 7 months ago
IncSpan: incremental mining of sequential patterns in large database
Many real life sequence databases, such as customer shopping sequences, medical treatment sequences, etc., grow incrementally. It is undesirable to mine sequential patterns from s...
Hong Cheng, Xifeng Yan, Jiawei Han
ALMOB
2006
80views more  ALMOB 2006»
13 years 7 months ago
Effective p-value computations using Finite Markov Chain Imbedding (FMCI): application to local score and to pattern statistics
The technique of Finite Markov Chain Imbedding (FMCI) is a classical approach to complex combinatorial problems related to sequences. In order to get efficient algorithms, it is k...
Grégory Nuel
IWCIA
2004
Springer
14 years 23 days ago
Performance Evaluation of Binarizations of Scanned Insect Footprints
The paper compares six conventional binarization methods for the special purpose of subsequent analysis of scanned insect footprints. We introduce a new performance criterion for p...
Young Woon Woo
KDD
2005
ACM
103views Data Mining» more  KDD 2005»
14 years 7 months ago
Fast discovery of unexpected patterns in data, relative to a Bayesian network
We consider a model in which background knowledge on a given domain of interest is available in terms of a Bayesian network, in addition to a large database. The mining problem is...
Szymon Jaroszewicz, Tobias Scheffer