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CIKM
2004
Springer
14 years 1 months ago
Scalable sequential pattern mining for biological sequences
Biosequences typically have a small alphabet, a long length, and patterns containing gaps (i.e., “don’t care”) of arbitrary size. Mining frequent patterns in such sequences ...
Ke Wang, Yabo Xu, Jeffrey Xu Yu
ICDM
2009
IEEE
145views Data Mining» more  ICDM 2009»
13 years 5 months ago
Significance of Episodes Based on Minimal Windows
Discovering episodes, frequent sets of events from a sequence has been an active field in pattern mining. Traditionally, a level-wise approach is used to discover all frequent epis...
Nikolaj Tatti
ICDM
2006
IEEE
166views Data Mining» more  ICDM 2006»
14 years 1 months ago
Mining Generalized Graph Patterns Based on User Examples
There has been a lot of recent interest in mining patterns from graphs. Often, the exact structure of the patterns of interest is not known. This happens, for example, when molecu...
Pavel Dmitriev, Carl Lagoze
KDD
2012
ACM
178views Data Mining» more  KDD 2012»
11 years 10 months ago
Differentially private transit data publication: a case study on the montreal transportation system
With the wide deployment of smart card automated fare collection (SCAFC) systems, public transit agencies have been benefiting from huge volume of transit data, a kind of sequent...
Rui Chen, Benjamin C. M. Fung, Bipin C. Desai, N&e...
KDD
2004
ACM
144views Data Mining» more  KDD 2004»
14 years 8 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