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- W1967593093 abstract "As a side effect of unprecedented amount of digitization of data, classical retrieval tools found themselves unable to go further beyond the tip of the Iceberg. Data Mining, with a clear promise to furnish adequate tools to do so, is the discovery of hidden information found in databases. In this paper, we are interested in presenting a thorough survey of Galois connection semantics-based approaches for mining association rules. We provide critical classification and comparison of theses algorithms based on criteria that we introduce to try to find an answer to the question: Does this novel approach avoid knowledge user-overwhelming?" @default.
- W1967593093 created "2016-06-24" @default.
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- W1967593093 date "2004-08-24" @default.
- W1967593093 modified "2023-09-27" @default.
- W1967593093 title "Approches d'extraction de règles d'association basées sur la correspondance de Galois" @default.
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