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Found 19 papers, 5 papers with code
INEXA: Interactive and Explainable Process Model Abstraction Through Object-Centric Process Mining
To enable the exploration of discovered process models at different granularity levels, we propose INEXA, an interactive, explainable process model abstraction method that keeps the link to the event log.
Identification of Regulatory Requirements Relevant to Business Processes: A Comparative Study on Generative AI, Embedding-based Ranking, Crowd and Expert-driven Methods
Organizations face the challenge of ensuring compliance with an increasing amount of requirements from various regulatory documents.
Large Process Models: Business Process Management in the Age of Generative AI
The continued success of Large Language Models (LLMs) and other generative artificial intelligence approaches highlights the advantages that large information corpora can have over rigidly defined symbolic models, but also serves as a proof-point of the challenges that purely statistics-based approaches have in terms of safety and trustworthiness.
Code Generation for Machine Learning using Model-Driven Engineering and SysML
Data-driven engineering refers to systematic data collection and processing using machine learning to improve engineering systems.
Model-Driven Engineering Method to Support the Formalization of Machine Learning using SysML
Results: By consolidating the knowledge of domain and machine learning experts, a powerful tool to describe machine learning tasks by formalizing knowledge using the systems modeling language SysML is introduced.
Model-Driven Engineering for Artificial Intelligence -- A Systematic Literature Review
Objective: This study aims to investigate the existing body of knowledge in the field of Model-Driven Engineering MDE in support of AI (MDE4AI) to sharpen future research further and define the current state of the art.
Conversational Process Modeling: Can Generative AI Empower Domain Experts in Creating and Redesigning Process Models?
Then a systematic literature review on conversational process modeling is performed, resulting in a taxonomy of application scenarios for conversational process modeling, including paraphrasing and improvement of process descriptions.
Preventing Object-centric Discovery of Unsound Process Models for Object Interactions with Loops in Collaborative Systems: Extended Version
Similar to classical process discovery, where we aim for behaviorally sound process models as a result, in OCPD, we aim for soundness of the resulting object-centric Petri nets.
An End-to-End Approach for Online Decision Mining and Decision Drift Analysis in Process-Aware Information Systems: Extended Version
Decision mining enables the discovery of decision rules from event logs or streams, and constitutes an important part of in-depth analysis and optimisation of business processes.
A Survey on Event Prediction Methods from a Systems Perspective: Bringing Together Disparate Research Areas
The diversity of application domains results in a diverse range of methods that are scattered across various research areas which, in turn, use different terminology for event prediction methods.
Predictive Compliance Monitoring in Process-Aware Information Systems: State of the Art, Functionalities, Research Directions
Process compliance can be checked during process design time based on verification of process models and at runtime based on monitoring the compliance states of running process instances.
Sustainability Through Cognition Aware Safety Systems -- Next Level Human-Machine-Interaction
Industrial Safety deals with the physical integrity of humans, machines and the environment when they interact during production scenarios.
Comparing decision mining approaches with regard to the meaningfulness of their results
Decisions and the underlying rules are indispensable for driving process execution during runtime, i. e., for routing process instances at alternative branches based on the values of process data.
The Role of Time and Data: Online Conformance Checking in the Manufacturing Domain
Secondly, it is investigated whether and how process mining supports domain experts during process monitoring as a secondary task.
Generating Reliable Process Event Streams and Time Series Data based on Neural Networks
Domains such as manufacturing and medicine crave for continuous monitoring and analysis of their processes, especially in combination with time series as produced by sensors.
Hiperfact: In-Memory High Performance Fact Processing -- Rethinking the Rete Inference Algorithm
The Rete forward inference algorithm forms the basis for many rule engines deployed today, but it exhibits the following problems: (1) the caching of all intermediate join results, (2) the processing of all rules regardless of the necessity to do so (stemming from the underlying forward inference approach), (3) not defining the join order of rules and its conditions, significantly affecting the final run-time performance, and finally (4) pointer chasing due to the overall network structure, leading to inefficient usage of the CPU caches caused by random access patterns.
Databases
Untangling the GDPR Using ConRelMiner
The General Data Protection Regulation (GDPR) poses enormous challenges on companies and organizations with respect to understanding, implementing, and maintaining the contained constraints.
Catalog of Formalized Application Integration Patterns
Enterprise application integration (EAI) solutions are the centrepiece of current enterprise IT architectures (e. g., cloud and mobile computing, business networks), however, require the formalization of their building blocks, represented by integration patterns, verification and optimization.
Software Engineering Logic in Computer Science
The NNN Formalization: Review and Development of Guideline Specification in the Care Domain
One way to address this challenge is to provide system-based support for nursing personnel in creating, executing, and adapting patient care processes.
