DISCOVERING FUZZY UNEXPECTED SEQUENCES WITH CONCEPT HIERARCHIES

DOI10.1142/S0218488509006054zbMath1193.68213OpenAlexW2155358511MaRDI QIDQ3638788

No author found.

Publication date: 28 October 2009

Published in: International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0218488509006054

zbMATH Keywords

data miningconcept hierarchiessoft hierarchy-based similarityunexpected sequences

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10) Knowledge representation (68T30)

Uses Software

• SPADE

Cites Work

• A new approach for discovering fuzzy quantitative sequential patterns in sequence databases
• Sequence data mining. Forward by Professor Jiawei Han
• Fuzzy sets
• A Fuzzy Data Mining Algorithm for Finding Sequential Patterns
• SPADE: An efficient algorithm for mining frequent sequences
• Data mining. Concepts and techniques

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