Information fusion from multiple databases using meta-association rules

DOI10.1016/j.ijar.2016.09.006zbMath1401.68268OpenAlexW2521205052WikidataQ58013189 ScholiaQ58013189MaRDI QIDQ2374520

Juan Gómez-Romero, Miguel Molina-Solana, M. Dolores Ruiz, María J. Martín-Bautista, Montserrat Ros

Publication date: 15 December 2016

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ijar.2016.09.006

zbMATH Keywords

association rulesinformation fusionfuzzy association ruleshigh order miningmeta-association rulesmultiple databases

Mathematics Subject Classification ID

Database theory (68P15) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

On indexing evidential data

Cites Work

• On a non-nested level-based representation of fuzziness
• A formal model for mining fuzzy rules using the RL representation theory
• Mining changes in association rules: a fuzzy approach
• Combined use of association rules mining and clustering methods to find relevant links between binary rare attributes in a large data set
• NEW APPROACHES FOR DISCOVERING EXCEPTION AND ANOMALOUS RULES
• STUDYING INTEREST MEASURES FOR ASSOCIATION RULES THROUGH A LOGICAL MODEL
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