# Flexible categorization for auditing using formal concept analysis and Dempster-Shafer theory

arXiv: https://arxiv.org/abs/2210.17330 · HTML: https://mlsanity.com/paper/2210.17330/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 82 references that are in the map.
- First posted on arXiv 31 Oct 2022.

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

- [Decision under Uncertainty](https://mlsanity.com/paper/1304.1527/) (2013)
- [Expert Opinion Extraction from a Biomedical Database](https://mlsanity.com/paper/1709.03270/) (2017)
- [The Dynamic of Belief in the Transferable Belief Model and Specialization-Generalization Matrices](https://mlsanity.com/paper/1303.5408/) (2013)
- [Rough concepts](https://mlsanity.com/paper/1907.00359/) (2019)
- [Toward a Dempster-Shafer theory of concepts](https://mlsanity.com/paper/1908.05145/) (2019)

## Built on by (most cited first, 3 of 3)

- [A Meta-Learning Algorithm for Interrogative Agendas](https://mlsanity.com/paper/2301.01837/) (2023)
- [Outlier detection using flexible categorisation and interrogative agendas](https://mlsanity.com/paper/2312.12010/) (2023)
- [Flexible categorization using formal concept analysis and Dempster-Shafer theory](https://mlsanity.com/paper/2408.15012/) (2024)

## Abstract (arXiv)

Categorization of business processes is an important part of auditing. Large amounts of transnational data in auditing can be represented as transactions between financial accounts using weighted bipartite graphs. We view such bipartite graphs as many-valued formal contexts, which we use to obtain explainable categorization of these business processes in terms of financial accounts involved in a business process by using methods in formal concept analysis. The specific explainability feature of the methodology introduced in the present paper provides several advantages over e.g.~non-explainable machine learning techniques, and in fact, it can be taken as a basis for the development of algorithms which perform the task of clustering on transparent and accountable principles. Here, we focus on obtaining and studying different ways to categorize according to different extents of interest in different financial accounts, or interrogative agendas, of various agents or sub-tasks in audit. We use Dempster-Shafer mass functions to represent agendas showing different interest in different set of financial accounts. We propose two new methods to obtain categorizations from these agendas. We also model some possible deliberation scenarios between agents with different interrogative agendas to reach an aggregated agenda and categorization. The framework developed in this paper provides a formal ground to obtain and study explainable categorizations from the data represented as bipartite graphs according to the agendas of different agents in an organization (e.g.~an audit firm), and interaction between these through deliberation.