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检索条件"丛书名=Lecture Notes in Business Information Processing"

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Enhancing API Labelling with BERT and GPT: An Exploratory Study 2nd

Enhancing API Labelling with BERT and GPT: An Exploratory St...

引用

28th International Conference on Enterprise Design Operations and Computing

作者： Morais, Gabriel Lemelin, Edwin Adda, Mehdi Bork, Dominik Univ Quebec Rimouski Levis PQ G6V 1L8 Canada Univ Laval Quebec City PQ G1V 0A6 Canada TU Wien Business Informat Grp Vienna Austria

ISBN: (纸本)9783031790584;9783031790591

Application Programming Interfaces (APIs) enable interaction, integration, and interoperability among applications and services, contributing to their adoption and proliferation. However, discovering APIs has relied on manual, time-consuming, costly processes that jeopardize their reuse potential and accentuate the need for effective API retrieval mechanisms. Leveraging the OpenAPI Specification as a basis, this paper presents an exploratory study that combines BERT and GPT machine learning models to propose a novel API classifier. Our investigation explored the zero-shot learning capabilities of GPT-4 and GPT-3.5 using relevant terms extracted from API descriptions using BERT. The evaluation of our approach on two datasets comprising 940 API descriptions sourced from public repositories yielded an F1-score of 100% in the small dataset (17 APIs) and 39.1% in the large dataset (923 APIs). These results surpass state-of-the-art on the small dataset with an impressive 29-point improvement. The large dataset showed GPT can suggest labels not in the provided list. Manual analysis revealed that GPT's suggested labels fit the API intent better in 18 out of 20 cases, highlighting its potential for unknown classes and mismatch detection. This emphasizes the need to improve dataset quality and availability for API research. Our findings show the potential of automated API retrieval and open avenues for future research.

关键词： API classification OpenAPI Specification GPT BERT

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Using Large Language Models to Generate Process Knowledge from Enterprise Content 22nd

Using Large Language Models to Generate Process Knowledge fr...

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22nd International Conference on business Process Management (BPM)

作者： Franzoi, Sandro Delwaulle, Maxime Dyong, Julian Schaffner, Jan Burger, Mara vom Brocke, Jan Univ Munster D-48149 Munster Germany ERCIS European Res Ctr Informat Syst D-48149 Munster Germany

ISBN: (纸本)9783031786655;9783031786662

Large language models (LLMs) have disrupted knowledge work in many application areas. Accordingly, the business Process Management (BPM) community has started to explore how LLMs can be leveraged, resulting in a variety of promising research directions across the BPM lifecycle. Despite rapid adoption in practice and strong research interest, however, little is known about the actual design of BPM systems that leverage LLMs in organizational contexts. In this paper, we report on design science-based research in collaboration with a large multinational company to design a BPM system that leverages LLMs for process knowledge extraction from diverse enterprise content. Based on the development of our prototype, we observe that LLMs provide the means to organize and generate process knowledge independent of specific forms of representation. We present a conceptual framework that describes the role of LLMs in generating process knowledge from diverse input formats and, in turn, making it available in diverse output formats via prompting, resulting in representation-agnostic process knowledge. We also highlight implications of our study for BPM research and practice.

关键词： Large Language Models Process Knowledge Generative Artificial Intelligence business Process Management

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Knowledge Graphs: A Key Technology for Explainable Knowledge-Aware Process Automation? 22nd

Knowledge Graphs: A Key Technology for Explainable Knowledge...

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22nd International Conference on business Process Management (BPM)

作者： Bein, Leon Pufahl, Luise Tech Univ Munich Sch Computat Informat & Technol Heilbronn Germany

ISBN: (纸本)9783031786655;9783031786662

Process automation is a key subfield of business process management. Recent advances in AI research promise to yield a new type of intelligent process automation that can support high-variability, flexible, knowledge-intensive processes previously hard to enhance with process automation. However, primarily proposed, subsymbolic deep learning approaches fail to reliably consider the complex knowledge inherent to these processes and provide adequate explanations for their decisions. Neuro-symbolic reasoning approaches based on knowledge graphs promise to address these challenges by allowing to holistically encode complex domain knowledge and to perform explainable reasoning thereupon. In this vision paper, we investigate the potential of knowledge graphs for intelligent process automation. Using tangible examples, we show how they can be used to enable explainable, knowledge-aware process automation, integrating a wide range of process knowledge. We show that such knowledge-aware process automation can contribute to addressing two current challenges of the BPM community: the automation of knowledge-intensive processes and the design of AI-augmented business process management systems. Finally, we discuss avenues for future research.

关键词： business Process Automation Knowledge Graphs Knowledge-intensive Processes Neuro-symbolic AI

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Process Mining Pipelines with Controlled Sharing of Data and Algorithms 22nd

Process Mining Pipelines with Controlled Sharing of Data and...

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22nd International Conference on business Process Management (BPM)

作者： Burattin, Andrea Kindler, Ekkart Dyhre, Nicholas Vestrup, Sebastian Zerbato, Francesca Weber, Barbara Tech Univ Denmark DTU Compute Lyngby Denmark Eindhoven Univ Technol Eindhoven Netherlands Univ St Gallen St Gallen Switzerland

ISBN: (纸本)9783031786655;9783031786662

Process mining leverages execution traces within an organisation's IT systems to gain insights into its processes. Despite being a mature discipline in academia and industry, setting up process mining pipelines is still a complex task and involves programming, manual steps, and considerations of privacy and intellectual property. This paper introduces a platform based on a distributed architecture that helps define, deploy, and execute process mining pipelines across organisations. The requirements for this distributed architecture and platform are derived from a set of process mining scenarios, whose relevance is validated through a survey. Furthermore, this paper introduces a prototype for an initial version of the platform, demonstrating feasibility and supporting the specified requirements.

关键词： Data Sharing

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Check My Flow: Distributed Conformance Checking at the Source 22nd

Check My Flow: Distributed Conformance Checking at the Sourc...

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22nd International Conference on business Process Management (BPM)

作者： Andersen, Julia Rathje, Patrick Landsiedel, Olaf Univ Kiel D-24118 Kiel Germany

ISBN: (纸本)9783031786655;9783031786662

IoT networks in, for example, smart manufacturing, smart homes, and smart health demand process mining beyond traditional event logs. However, conventional process discovery and conformance checking algorithms expect data to be collected at a central location for mining. As a result, they struggle to handle the vast amounts of data generated by IoT networks, which often leads to privacy concerns. To address these challenges, this paper introduces Distributed Conformance Checking (DisCC). DisCC leverages a footprint-fitness method to perform distributed online conformance checks directly at the data source where an event is sensed, ensuring scalable conformance checking and enabling privacy by only sharing aggregated event data with a central entity. Our evaluation of DisCC demonstrates its effectiveness in accurately performing conformance checks at the event, trace, and log levels. We experimentally show the correctness of DisCC and how quickly its interim results converge to the correct fitness value. The system supports real-time alerts for non-conforming events and traces, detects concept drifts and temporary fitness losses through a sliding window implementation, and offers a scalable, privacy-enabling solution for process monitoring in IoT networks.

关键词： Online Conformance Checking Distributed Process Mining Event Data Stream Scalability

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The business Process Optimization Competition 22nd

The Business Process Optimization Competition

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22nd International Conference on business Process Management (BPM)

作者： Schumann, Felix Ehrendorfer, Matthias Kunkler, Michel Busch, Kiran Leopold, Henrik Urny, Leon Schmauch, Martin Rodzik, Olga Lanz, Stefanie Tiras, Efe Al-Zamkan, Amgad El Kari, Jana Dijkman, Remco Tech Univ Munich TUM Sch Computat Informat & Technol Garching Germany Kuhne Logist Univ Hamburg Germany Eindhoven Univ Technol Eindhoven Netherlands

ISBN: (纸本)9783031786655;9783031786662

Optimizing organizational operations with respect to different decisions and to achieve a variety of objectives has been thoroughly studied. Examples include deciding which transport order to assign to which truck in order to minimize costs or deciding on how much stock to keep of a particular product in order to balance costs and delivery reliability. business processes bring unique challenges to optimization problems, due to the complexity and uncertainty of the interdependencies between their tasks. The business process optimization competition presented such an optimization problem. Participants had to develop an algorithm that decided when to admit patients for hospital treatment, with various uncertain treatment tasks ahead. Eight different algorithms were submitted and compared to identify the most effective types of algorithm for business process optimization. Four algorithms outperformed the heuristic benchmark, with two of these being reinforcement learning algorithms. This suggests that reinforcement learning is a promising approach for optimizing business processes.

关键词： business Process Optimization Heuristics

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Ad-Hoc Subprocesses - The Missing Link Between Scheduling and business Process Modelling 22nd

Ad-Hoc Subprocesses - The Missing Link Between Scheduling an...

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22nd International Conference on business Process Management (BPM)

作者： Goel, Asvin Kuhne Logist Univ Hamburg Germany

ISBN: (纸本)9783031786655;9783031786662

This paper aims at bridging the gap between scheduling and business process modeling, two fields that have evolved independently from each other, even though both share common goals, i.e., the improvement of business operations. The paper shows how BPMN 2.0 can be used to model scheduling problems using a BPMN element that is often overlooked: ad-hoc subprocesses. It shows how ad-hoc subprocesses provide the basis for modeling scheduling requirements and demonstrates how well-known scheduling problems, such as the travelling salesperson problem and the job shop scheduling problem can be represented as BPMN models. business problems containing scheduling problems can be directly modelled by domain experts and process owners, eliminating the need to consult experts in mathematical programming. Moreover, new avenues are opened for research in optimisation algorithms capable of operating directly on BPMN models.

关键词： BPMN 2.0 Modelling Optimisation

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Conceptualizing Change Activities in Process Mining 2nd

Conceptualizing Change Activities in Process Mining

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28th International Conference on Enterprise Design Operations and Computing

作者： Knoblich, Steven Pfahlsberger, Lukas Mendling, Jan Humboldt Univ Rudower Chaussee 25 D-12489 Berlin Germany

ISBN: (纸本)9783031790584;9783031790591

In an increasingly dynamic world, business processes must be able to respond to frequently occurring and random changes during their execution. Consequently, this means that the process models must be able to handle this complexity and enable process analysts to derive the right conclusions quickly. However, current approaches in the field of process mining do not distinguish between process activities associated with change and those with routine. This condition leads to more complicated, overloaded, and sometimes misguided process visualizations that make it difficult for analysts to evaluate them. In this paper, we address the research problem by conceptualizing a new type of process activity that we call change activity which we base on causal knowledge. We thereby extend the causal process mining approach with another important aspect for handling random occurrences of events. We evaluated our findings through a survey of process mining experts from research and practice. Our results indicate that a dedicated visualization of change activities reduces the complexity of process visualizations. In addition, unimportant information is hidden and important information is highlighted so that analysts can make better assessments.

关键词： Change Activities Causal Process Mining Visual Analytics

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Introducing Variables to Data Objects in BPMN 2nd

Introducing Variables to Data Objects in BPMN

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28th International Conference on Enterprise Design Operations and Computing

作者： Koenig, Maximilian Lichtenstein, Tom Seidel, Anjo Weske, Mathias Univ Potsdam Hasso Plattner Inst Potsdam Germany

ISBN: (纸本)9783031790584;9783031790591

The management of data is crucial in today's organizations, making it necessary to specify exactly how data is created, accessed, and manipulated during business process enactment. Given the importance of data, it comes as a surprise that approaches like BPMN only provide limited support for modeling data and how it is read and written. In particular, they cannot represent multiple data objects of the same type, and they lack concise semantics for multi-instance data objects. Against this background, this paper proposes an extension to BPMN process models by introducing variable identifiers to distinguish individual data objects of the same class in a given process. The behavior is detailed using translational semantics to Colored Petri nets, and a set of verification mechanisms is presented that allow for a more precise analysis of data objects in business processes.

关键词： BPMN Data in Processes Translational Semantics Colored Petri Nets Variables

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Unraveling the Never-Ending Story of Lifecycles and Vitalizing Processes 2nd

Unraveling the Never-Ending Story of Lifecycles and Vitalizi...

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28th International Conference on Enterprise Design Operations and Computing

作者： Fahrenkrog-Petersen, Stephan A. Bala, Saimir Pufahl, Luise Mendling, Jan Weizenbaum Inst Networked Soc Berlin Germany Humboldt Univ Berlin Germany Tech Univ Munich Heilbronn Germany Vienna Univ Econ & Business Adm Vienna Austria

ISBN: (纸本)9783031790584;9783031790591

business process management (BPM) has been widely used to discover, model, analyze, and optimize organizational processes. BPM looks at these processes with analysis techniques that assume a clearly defined start and end. However, not all processes adhere to this logic, with the consequence that their behavior cannot be appropriately captured by BPM analysis techniques. This paper addresses this research problem at a conceptual level. More specifically, we introduce the notion of vitalizing business processes that target the lifecycle process of one or more entities. We show the existence of lifecycle processes in many industries and that their appropriate conceptualizations pave the way for the definition of suitable modeling and analysis techniques. This paper provides a set of requirements for their analysis, and a conceptualization of lifecycle and vitalizing processes.

关键词： business Process Management Types of Processes Process Analysis Process Models Lifecycle

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