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» Mining Closed Episodes from Event Sequences Efficiently
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SIGMOD
2008
ACM
136views Database» more  SIGMOD 2008»
14 years 7 months ago
Mining relationships among interval-based events for classification
Existing temporal pattern mining assumes that events do not have any duration. However, events in many real world applications have durations, and the relationships among these ev...
Dhaval Patel, Wynne Hsu, Mong-Li Lee
TCSV
2008
150views more  TCSV 2008»
13 years 7 months ago
Mining Recurring Events Through Forest Growing
Recurring events are short temporal patterns that consist of multiple instances in the target database. Without any a priori knowledge of the recurring events, in terms of their le...
Junsong Yuan, Jingjing Meng, Ying Wu, Jiebo Luo
SAC
2011
ACM
12 years 10 months ago
RuleGrowth: mining sequential rules common to several sequences by pattern-growth
Mining sequential rules from large databases is an important topic in data mining fields with wide applications. Most of the relevant studies focused on finding sequential rules a...
Philippe Fournier-Viger, Roger Nkambou, Vincent Sh...
ADMA
2009
Springer
186views Data Mining» more  ADMA 2009»
14 years 2 months ago
Mining Compressed Repetitive Gapped Sequential Patterns Efficiently
Mining frequent sequential patterns from sequence databases has been a central research topic in data mining and various efficient mining sequential patterns algorithms have been p...
Yongxin Tong, Zhao Li, Dan Yu, Shilong Ma, Zhiyuan...
SDM
2010
SIAM
283views Data Mining» more  SDM 2010»
13 years 9 months ago
Cascading Spatio-temporal Pattern Discovery: A Summary of Results
Given a collection of Boolean spatio-temporal(ST) event types, the cascading spatio-temporal pattern (CSTP) discovery process finds partially ordered subsets of event-types whose ...
Pradeep Mohan, Shashi Shekhar, James A. Shine, Jam...