mlsanityData to 14 Oct 2026

Recent Advances in Data-Driven Business Process Management

arXiv 2406.01786 ↗First posted 3 Jun 2024cs.DB cs.AIcited by 2

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Abstract (arXiv)

The rapid development of cutting-edge technologies, the increasing volume of data and also the availability and processability of new types of data sources has led to a paradigm shift in data-based management and decision-making. Since business processes are at the core of organizational work, these developments heavily impact BPM as a crucial success factor for organizations. In view of this emerging potential, data-driven business process management has become a relevant and vibrant research area. Given the complexity and interdisciplinarity of the research field, this position paper therefore presents research insights regarding data-driven BPM.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 22 of its 116 references that are in the map. First posted on arXiv 3 Jun 2024.

Builds on

22 of 116 references.

References · 22

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2022From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AIcited by 302
  3. 2023Generative AIcited by 120
  4. 2016Predictive Business Process Monitoring with LSTM Neural Networkscited by 104
  5. 2016Predicting Process Behaviour using Deep Learningcited by 60
  6. 2020Deep Learning for Predictive Business Process Monitoring: Review and Benchmarkcited by 45
  7. 2018Survey and cross-benchmark comparison of remaining time prediction methods in business process monitoringcited by 43
  8. 2020Fine-tuning BERT for Low-Resource Natural Language Understanding via Active Learningcited by 25
  9. 2020Prescriptive Business Process Monitoring for Recommending Next Best Actionscited by 22
  10. 2018Alarm-Based Prescriptive Process Monitoringcited by 16
  11. 2019An Approach for Process Model Extraction By Multi-Grained Text Classificationcited by 16
  12. 2021Prescriptive Process Monitoring: Quo Vadis?cited by 15
10 more
  1. 2022PET: An Annotated Dataset for Process Extraction from Natural Language Textcited by 15
  2. 2023ProcessGPT: Transforming Business Process Management with Generative Artificial Intelligencecited by 11
  3. 2023Beyond Rule-based Named Entity Recognition and Relation Extraction for Process Model Generation from Natural Language Textcited by 8
  4. 2021Evaluating Predictive Business Process Monitoring Approaches on Small Event Logscited by 6
  5. 2020Shedding Light on Blind Spots: Developing a Reference Architecture to Leverage Video Data for Process Miningcited by 5
  6. 2022Predictive Compliance Monitoring in Process-Aware Information Systems: State of the Art, Functionalities, Research Directionscited by 5
  7. 2023Process Mining for Unstructured Data: Challenges and Research Directionscited by 4
  8. 2022Can recurrent neural networks learn process model structure?cited by 3
  9. 2020A framework to evaluate the viability of robotic process automation for business process activitiescited by 2
  10. 2020On the Composition of the Long Tail of Business Processes: Implications from a Process Mining Studycited by 1

Built on by

Cited by year

Citing papers per year: 2024: 1; 2025: 1.

2 papers.

  1. 2024Assisted Data Annotation for Business Process Information Extraction from Textual Documentscited by 0
  2. 2025FairLoop: Software Support for Human-Centric Fairness in Predictive Business Process Monitoringcited by 0