Efficiently mining cohesion-based patterns and rules in event sequences

DOI10.1007/s10618-019-00628-0zbMath1458.68161OpenAlexW2935741862MaRDI QIDQ2218356

Boris Cule, Len Feremans, Bart Goethals

Publication date: 15 January 2021

Published in: Data Mining and Knowledge Discovery (Search for Journal in Brave)

Full work available at URL: https://hdl.handle.net/10067/1613030151162165141

zbMATH Keywords

sequential patternsassociation rulescohesive itemsetsepisodes

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Uses Software

• SPADE
• PrefixSpan
• BIDE

Cites Work

• Unnamed Item
• Discovering episodes with compact minimal windows
• Ranking episodes using a partition model
• Skopus: mining top-\(k\) sequential patterns under leverage
• Mining closed strict episodes
• Mining Compressing Sequential Patterns
• MARBLES: Mining association rules buried in long event sequences
• SPADE: An efficient algorithm for mining frequent sequences

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