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» Incremental Mining of Sequential Patterns in Large Databases
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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
2003
SIAM
183views Data Mining» more  SDM 2003»
13 years 8 months ago
ApproxMAP: Approximate Mining of Consensus Sequential Patterns
Conventional sequential pattern mining methods may meet inherent difficulties in mining databases with long sequences and noise. They may generate a huge number of short and trivi...
Hye-Chung Kum, Jian Pei, Wei Wang 0010, Dean Dunca...
ESWA
2006
139views more  ESWA 2006»
13 years 7 months ago
An efficient data mining approach for discovering interesting knowledge from customer transactions
Mining association rules and mining sequential patterns both are to discover customer purchasing behaviors from a transaction database, such that the quality of business decision ...
Show-Jane Yen, Yue-Shi Lee
EUROPAR
2001
Springer
13 years 12 months ago
Parallel Tree Projection Algorithm for Sequence Mining
Discovery of sequential patterns is becoming increasingly useful and essential in many scienti c and commercial domains. Enormous sizes of available datasets and possibly large nu...
Valerie Guralnik, Nivea Garg, George Karypis
PPOPP
2005
ACM
14 years 1 months ago
A sampling-based framework for parallel data mining
The goal of data mining algorithm is to discover useful information embedded in large databases. Frequent itemset mining and sequential pattern mining are two important data minin...
Shengnan Cong, Jiawei Han, Jay Hoeflinger, David A...