Publication: Mining negative rules: a literature review focusing on performance
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Date
2021-01-01
Advisor
Coadvisor
Graduate program
Undergraduate course
Journal Title
Journal ISSN
Volume Title
Publisher
Ieee
Type
Work presented at event
Access right
Abstract
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.
Description
Language
Portuguese
Citation
Proceedings Of 2021 16th Iberian Conference On Information Systems And Technologies (cisti'2021). New York: Ieee, 6 p., 2021.
