# Process Mining for Unstructured Data: Challenges and Research Directions

arXiv: https://arxiv.org/abs/2401.13677 · HTML: https://mlsanity.com/paper/2401.13677/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 45 references that are in the map.
- First posted on arXiv 30 Nov 2023.

## Builds on (most cited first, 10 of 10)

- [Image and Video Compression with Neural Networks: A Review](https://mlsanity.com/paper/1904.03567/) (2019)
- [Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring](https://mlsanity.com/paper/2009.02098/) (2020)
- [ProgDTD: Progressive Learned Image Compression with Double-Tail-Drop Training](https://mlsanity.com/paper/2305.02145/) (2023)
- [Event Abstraction for Process Mining using Supervised Learning Techniques](https://mlsanity.com/paper/1606.07283/) (2016)
- [Privacy and Confidentiality in Process Mining -- Threats and Research Challenges](https://mlsanity.com/paper/2106.00388/) (2021)
- [Shedding Light on Blind Spots: Developing a Reference Architecture to Leverage Video Data for Process Mining](https://mlsanity.com/paper/2010.11289/) (2020)
- [PROVED: A Tool for Graph Representation and Analysis of Uncertain Event Data](https://mlsanity.com/paper/2103.05564/) (2021)
- [Event-Case Correlation for Process Mining using Probabilistic Optimization](https://mlsanity.com/paper/2206.10009/) (2022)
- [SKTR: Trace Recovery from Stochastically Known Logs](https://mlsanity.com/paper/2206.12672/) (2022)
- [Probabilistic and Non-Deterministic Event Data in Process Mining: Embedding Uncertainty in Process Analysis Techniques](https://mlsanity.com/paper/2205.04827/) (2022)

## Built on by (most cited first, 4 of 4)

- [Recent Advances in Data-Driven Business Process Management](https://mlsanity.com/paper/2406.01786/) (2024)
- [Ranking the Top-K Realizations of Stochastically Known Event Logs](https://mlsanity.com/paper/2410.00067/) (2024)
- [All Eyes on the Workflow: Automated and Efficient Event Discovery from Video Streams](https://mlsanity.com/paper/2604.22476/) (2026)
- [Interpretable experiential learning based on state history and global feedback](https://mlsanity.com/paper/2605.00940/) (2026)

## Abstract (arXiv)

The application of process mining for unstructured data might significantly elevate novel insights into disciplines where unstructured data is a common data format. To efficiently analyze unstructured data by process mining and to convey confidence into the analysis result, requires bridging multiple challenges. The purpose of this paper is to discuss these challenges, present initial solutions and describe future research directions. We hope that this article lays the foundations for future collaboration on this topic.