Abstract
Business process compliance has become a crucial aspect for companies due to severe fines that can be imposed if constraints and rules emerging from regulatory documents are violated. Regulatory docu- ments are often written in natural language and analyzing them is mainly done manually since only limited tool support is available. Therefore, we present RegMiner, a web service for discovering and visualizing con- straints from regulatory documents. By employing NLP and data min- ing techniques, compliance constraints can be automatically extracted, grouped, and visualized leading to a separation of relevant and non- relevant document parts and insights into, e.g., duties of stakeholders. A case study based on a current document from the European parliament regarding the financial domain demonstrates RegMiner's maturity.
Original language | English |
---|---|
Pages (from-to) | 112-116 |
Number of pages | 5 |
Journal | CEUR Workshop Proceedings |
Volume | 2673 |
State | Published - 2020 |
Externally published | Yes |
Event | 2020 Best Dissertation Award, Doctoral Consortium, and Demonstration and Resources Track at BPM, BPM-D 2020 - Sevilla, Spain Duration: 13 Sep 2020 → 18 Sep 2020 |
Keywords
- Business Process Compliance
- Natural Language Processing
- Regulatory Documents