# Uncertain Case Identifiers in Process Mining: A User Study of the Event-Case Correlation Problem on Click Data

arXiv: https://arxiv.org/abs/2204.04164 · HTML: https://mlsanity.com/paper/2204.04164/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 19 references that are in the map.
- First posted on arXiv 8 Apr 2022.

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

- [Distributed Representations of Words and Phrases and their Compositionality](https://mlsanity.com/paper/1310.4546/) (2013)
- [Conformance Checking over Uncertain Event Data](https://mlsanity.com/paper/2009.14452/) (2020)
- [Probability Estimation of Uncertain Process Trace Realizations](https://mlsanity.com/paper/2108.08615/) (2021)
- [PROVED: A Tool for Graph Representation and Analysis of Uncertain Event Data](https://mlsanity.com/paper/2103.05564/) (2021)
- [Identifying candidate routines for Robotic Process Automation from unsegmented UI logs](https://mlsanity.com/paper/2008.05782/) (2020)

## Built on by (most cited first, 2 of 2)

- [Performance-Preserving Event Log Sampling for Predictive Monitoring](https://mlsanity.com/paper/2301.07624/) (2023)
- [Resolving Uncertain Case Identifiers in Interaction Logs: A User Study](https://mlsanity.com/paper/2212.00009/) (2022)

## Abstract (arXiv)

Among the many sources of event data available today, a prominent one is user interaction data. User activity may be recorded during the use of an application or website, resulting in a type of user interaction data often called click data. An obstacle to the analysis of click data using process mining is the lack of a case identifier in the data. In this paper, we show a case and user study for event-case correlation on click data, in the context of user interaction events from a mobility sharing company. To reconstruct the case notion of the process, we apply a novel method to aggregate user interaction data in separate user sessions-interpreted as cases-based on neural networks. To validate our findings, we qualitatively discuss the impact of process mining analyses on the resulting well-formed event log through interviews with process experts.