A comprehensive review of visualization methods for association rule mining: Taxonomy, Challenges, Open problems and Future ideas
February 24, 2023 Β· The Cartographer Β· π Expert systems with applications
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"Title-pattern auto-detect: A comprehensive review of visualization methods for association rule mining: Taxonomy, Challenges, O"
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Authors
Iztok Fister, Iztok Fister, DuΕ‘an Fister, Vili Podgorelec, Sancho Salcedo-Sanz
arXiv ID
2302.12594
Category
cs.DB: Databases
Cross-listed
cs.AI
Citations
30
Venue
Expert systems with applications
Last Checked
9 days ago
Abstract
Association rule mining is intended for searching for the relationships between attributes in transaction databases. The whole process of rule discovery is very complex, and involves pre-processing techniques, a rule mining step, and post-processing, in which visualization is carried out. Visualization of discovered association rules is an essential step within the whole association rule mining pipeline, to enhance the understanding of users on the results of rule mining. Several association rule mining and visualization methods have been developed during the past decades. This review paper aims to create a literature review, identify the main techniques published in peer-reviewed literature, examine each method's main features, and present the main applications in the field. Defining the future steps of this research area is another goal of this review paper.
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