A5041924999- Business Process Modeling and Analysis
- Semantic Web and Ontologies
- Service-Oriented Architecture and Web Services
- Data Quality and Management
- Big Data and Business Intelligence
- Robotic Process Automation Applications
- Software Engineering Research
- Software System Performance and Reliability
- Information Technology Governance and Strategy
- Corporate Governance and Management
- Supply Chain Resilience and Risk Management
- Advanced Data Processing Techniques
- Flexible and Reconfigurable Manufacturing Systems
- Digital Innovation in Industries
- Information and Cyber Security
- Manufacturing Process and Optimization
- Explainable Artificial Intelligence (XAI)
- Green IT and Sustainability
- Safety Systems Engineering in Autonomy
- Environmental Monitoring and Data Management
- Occupational Health and Safety Research
- Scientific Computing and Data Management
- Digital Transformation in Industry
- Artificial Intelligence in Healthcare
- Cloud Data Security Solutions
University of Mannheim
2020-2024
Saarland University
2016-2020
University of Notre Dame
2020
German Research Centre for Artificial Intelligence
2015-2020
Universidad de Sevilla
2019
AI-augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems, empowered by trustworthy AI technology. An ABPMS enhances the execution business processes with aim making these more adaptable, proactive, explainable, and context-sensitive. This manifesto presents a vision for ABPMSs discusses research challenges that need to be surmounted realize this vision. To end, we define concept ABPMS, outline lifecycle within discuss core...
Abstract Studying the behavior of users in software systems has become an essential task for vendors who want to mitigate usability problems and identify automation potentials, or researchers test behavioral theories. One approach studying user a data-driven way is through analysis so-called interaction (UI) logs, which record low-level activities that performs while executing task. In paper, authors refer UI logs as User Behavior Mining (UBM) position it research topic. UBM conceptualized...
User interaction (UI) logs are high-resolution event that record low-level activities performed by a user during the execution of task in an information system. Each such log represents between and interface, as clicking button, ticking checkbox, or typing into text field. UI used many different application contexts for purposes usability analysis, mining, robotic process automation (RPA). However, suffer from lack standardization. research study processing tool relies on conceptualization...
The goal of process discovery is to visualize event log data as a model. In reality, however, these models are often highly complex. Process trace clustering well-studied and powerful technique address this. It groups an into more cohesive sub logs, such that the discovered become less complex easier understand. Over past 15 years, researchers proposed various approaches for in discovery. developed vary greatly with regard algorithmic capacities, characteristics, computational complexity,...
Abstract The advent of Industry 4.0 is expected to dramatically change the manufacturing industry as we know it today. Highly standardized, rigid processes need become self-organizing and decentralized. This flexibility leads new challenges management smart factories in general production planning control particular. In this contribution, illustrate how established techniques from Business Process Management (BPM) hold great potential conquer 4.0. Therefore, show three application cases...
Conformance checking is a major function of process mining, which allows organizations to identify and alleviate potential deviations from the intended behavior. To fully leverage its benefits, it important that conformance results are visualized in way approachable understandable for non-expert users. However, visualization has so far not been widely considered research. Therefore, goal this paper develop an understanding how by mining tools provide foundation further research on topic. We...
Mobile robots can provide significant operational advantages in emergency response missions. With increasing autonomy need knowledge of the current mission order to be able properly contribute it. We propose acquire by interpreting verbal communication among human response-team members and use process mining techniques ground interpretations analyses data corresponding reference models. also present a novel concept assistance that uses acquired support first responders' work processes both...
Business Process Management (BPM) aims to improve organizational activities and their outcomes by managing the underlying processes. To achieve this, it is often necessary consider information from various sources, including unstructured textual documents. Therefore, researchers have developed several BPM-specific solutions that extract documents using Natural Language Processing techniques. These are specific respective tasks cannot accomplish multiple process-related problems as a...
Predicting the next activity of a running process is an important aspect management. Recently, artificial neural networks, so called deep-learning approaches, have been proposed to address this challenge. This demo paper describes software application that applies Tensorflow framework prediction. The reads industry-standard XES files for training and presents user with easy-to-use graphical interface both system provides several improvements over earlier work. focuses on implementation...