# A comprehensive review of visualization methods for association rule mining: Taxonomy, Challenges, Open problems and Future ideas

arXiv: https://arxiv.org/abs/2302.12594 · HTML: https://mlsanity.com/paper/2302.12594/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 80 references that are in the map.
- First posted on arXiv 24 Feb 2023.

## Builds on (most cited first, 5 of 5)

- [Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI](https://mlsanity.com/paper/1910.10045/) (2019)
- [A Practical guide on Explainable AI Techniques applied on Biomedical use case applications](https://mlsanity.com/paper/2111.14260/) (2021)
- [Information cartography in association rule mining](https://mlsanity.com/paper/2003.00348/) (2020)
- [Association rules over time](https://mlsanity.com/paper/2010.03834/) (2020)
- [uARMSolver: A framework for Association Rule Mining](https://mlsanity.com/paper/2010.10884/) (2020)

## Built on by (most cited first, 1 of 1)

- [Numerical Association Rule Mining: A Systematic Literature Review](https://mlsanity.com/paper/2307.00662/) (2023)

## Abstract (arXiv)

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.