Mining negative rules: A literature review focusing on performance - Colombo, Alexandre [UNESP]; Spolon, Roberta [UNESP]; Lobato, Renata Spolon [UNESP]; Manacero, Aleardo [UNESP]; Cavenaghi, Marcos Antonio (Institute of Electrical and Electronics Engineers (IEEE), 2021)
Mining of frequent patterns and association rules is a Data Mining task that aims to determine consistent relationships among elements in a transaction database. Algorithms that consider the absence of elements perform the generation of so-called negative rules which result in associations of great interest for some applications, enabling it to obtain extra knowledge in comparison to the positive case. This type of association presents a problem regarding the increased amount of generated rules which demands adequate computational resources. This study presents a systematic review with the aim of grouping the concepts of the main contemporary works on this topic, in order to assist the development of future works in this subject.
Mineração de regras negativas: uma revisão da literatura com foco em desempenho
Keywords: data mining; frequent patterns; negative association rules; parallel algorithms; systematic literature review