Resumo

DIAZ VERA, Julio César; NEGRIN ORTIZ, Guillermo Manuel; MOLINA, Carlos  e  VILA, María Amparo. Size reduction in Association Rules Models: A systematic literature review. Rev cuba cienc informat [online]. 2021, vol.15, n.3, pp. 153-174.  Epub 01-Set-2021. ISSN 2227-1899.

Association Rules are one of the most studied and applied techniques in Data Mining. This is because they are easily accepted an interpreted by human agents. Association Rules main handicap is the great cardinality of models that even in simple datasets produce too many rules to be, manually, analyzed by experts in order to find those that are relevant ones. The objective of this paper is to carry out a systematic literature review in the field of size reduction in association rules models, to characterize and present the state of the art of this field. From the analysis of the results, it could be observed that most works focus on redundancy elimination but they are moving from redundancy definition associated to rule structure to redundancy definitions based on user knowledge and preference.

Palavras-chave : association rules; size reduction in association rules models; systematic literature review.

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