Approches d'extraction de règles d'association basées sur la correspondance de Galois

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? MOTS-CLÉS : fouille de données, analyse de concepts formels, règles d’associations.