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Process Modeling with Large Language Models 25th

Process Modeling with Large Language Models

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25th International Working Conference on business Process Modeling, Development, and Support (BPMDS) / 29th International Working Conference on Exploring Modeling Methods for Systems Analysis and Development (EMMSAD)

作者： Kourani, Humam Berti, Alessandro Schuster, Daniel van der Aalst, Wil M. P. Fraunhofer Inst Appl Informat Technol FIT St Augustin Germany Rhein Westfal TH Aachen Aachen Germany

ISBN: (纸本)9783031610066;9783031610073

In the realm of business Process Management (BPM), process modeling plays a crucial role in translating complex process dynamics into comprehensible visual representations, facilitating the understanding, analysis, improvement, and automation of organizational processes. Traditional process modeling methods often require extensive expertise and can be time-consuming. This paper explores the integration of Large Language Models (LLMs) into process modeling to enhance the accessibility of process modeling, offering a more intuitive entry point for non-experts while augmenting the efficiency of experts. We propose a framework that leverages LLMs for the automated generation and iterative refinement of process models starting from textual descriptions. Our framework involves innovative prompting strategies for effective LLM utilization, along with a secure model generation protocol and an error-handling mechanism. Moreover, we instantiate a concrete system extending our framework. This system provides robust quality guarantees on the models generated and supports exporting them in standard modeling notations, such as the business Process Modeling Notation (BPMN) and Petri nets. Preliminary results demonstrate the framework's ability to streamline process modeling tasks, underscoring the transformative potential of generative AI in the BPM field.

关键词： Process Modeling business Process Management Generative AI Large Language Models

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Innovation Process Integration Challenges and Their Influence on Project Management Performance in Oil and Gas Field- A Conceptual Framework Development 20th

Innovation Process Integration Challenges and Their Influenc...

引用

20th European, Mediterranean, and Middle Eastern Conference (EMCIS)

作者： Basioni, Ahmed British Univ Fac Business & Law Dubai U Arab Emirates

ISBN: (纸本)9783031564802;9783031564819

Purpose - This paper aims to develop a comprehensive conceptual framework that elucidates the multifaceted factors affecting the dissemination of innovation processes within the oil and gas sector and how they interplay to impact project management, ultimately leading to improved project performance Methodology - This study employs a literature synthesis method to build the conceptual framework. Findings - The forthcoming study outcomes will help pinpoint the principal barriers to and catalysts for implementing innovation systems within the oil and gas industry's ecosystem. Implications - Conducting subsequent research on integrating the concept of "green innovation" is pivotal for confirming the feasibility of constructing a conceptual framework encompassing critical variables that impact the adoption of innovation processes within the energy sector. Originality - Exploring the interplay between the innovation process, project management, and performance contributes to a more comprehensive comprehension of a sustainable innovation process that bolsters the expansion of the oil and gas sector.

关键词： Innovation Process organization Oil Performance

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Zero-Inflated Poisson Tensor Factorization for Sparse Purchase Data in E-Commerce Markets 11th

Zero-Inflated Poisson Tensor Factorization for Sparse Purcha...

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11th International Conference on Industrial Engineering and Applications - Europe (ICIEA - Europe)

作者： Mizutani, Keisuike Ueta, Ayaka Ueda, Ryota Oishi, Ray Hara, Tomofumi Hoshino, Yuki Kobayashi, Ken Nakata, Kazuhide Tokyo Inst Technol Tokyo Japan

ISBN: (纸本)9783031581120;9783031581137

Nonnegative tensor factorization (NTF) plays a crucial role in extracting latent factors and predicting future sales from purchase data consisting of user and item attributes. However, the increase in these attributes leads to tensor data becoming sparse, causing a reduction in decomposition accuracy. For example, when there are numerous combinations of unavailable item genres and prices, the purchase history data becomes sparse and follows a distribution where all its elements are zero. To address this issue, we propose a novel NTF method assuming zero-inflated Poisson (ZIP) distribution based on Expectation-Maximization (EM) algorithm. This enables us to effectively handle sparsity in high-dimensional multiway data and identify combinations of user and item attributes that are potentially not likely to be purchased. We verified the effectiveness of the proposed approach through numerical experiments using real-world e-commerce data. The results showed our proposed ZIP model outperforms existing methods in both in-sample and out-of-sample experiments. Moreover, the proposed method qualitatively demonstrated the effectiveness of handling sparsity.

关键词： tensor factorization zero-inflated Poisson distribution e-commerce

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Dealing with Emotional Requirements for Software Ecosystems: Findings and Lessons Learned in the PHArA-ON Project 18th

Dealing with Emotional Requirements for Software Ecosystems:...

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18th International Conference on Research Challenges in information Sciences (RCIS)

作者： Gharib, Mohamad Falco, Mariana Nijboer, Femke Tinga, Angelica M. D'Agostini, Stefania Rovini, Erika Fiorini, Laura Cavallo, Filippo Taveter, Kuldar Univ Tartu Tartu Estonia Univ Twente Enschede Netherlands Engn Ingn Informat Rome Italy Univ Florence Florence Italy

ISBN: (纸本)9783031594649;9783031594656

Requirements Engineering (RE) stands as the cornerstone in ensuring that a system comprehensively captures and analyzes the needs and expectations of its users and stakeholders. Despite the numerous approaches designed for dealing with functional and quality (nonfunctional) requirements, approaches for dealing with emotional requirements still lag. Emotional requirements capture how users should feel when using a system, and inadequate consideration of such requirements results in end-users reluctance to use the system. In this paper, we report on our experience in dealing with emotional requirements as part of an H2020 European Project, namely PHArA-ON (Pilots for Healthy and Active Ageing in Europe) for the development of the PHArA-ON ecosystem that aims at improving the well-being and active aging of older adults. Specifically, we present the process we followed for dealing with emotional requirements, and we summarize the findings and lessons learned from this experience.

关键词： Emotional Requirements Emotions Goal Modeling Ecosystems Requirements Engineering

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The Know-How of Agile Retrospectives in Software Startups

The Know-How of Agile Retrospectives in Software Startups

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24th International Conference on Agile Software Development (XP)

作者： Khanna, Dron Wang, Xiaofeng Free Univ Bolzano I-39100 Bolzano Italy

ISBN: (纸本)9783031485497;9783031485503

Software startups are responsible for fast product delivery to the market. To aid this process, a retrospective inside a startup team can be very fruitful for software development. The traditional way of conducting agile retrospectives involves discussion based on what went well, what did not go well, and how to improve the software development cycle helps to save resources, get directed toward the startup vision, and overcome several challenges. To attain insights about the agile retrospective approach in startups, we studied the following question: How are software startups performing agile retrospectives? Hence, we conducted seven multiple case studies with 19 semi-structured interviews that lasted 30-65 min. The results outline that all software startups prefer a reflection through agile retrospectives but not in the traditional manner. Due to the startup's casual and less restricted working environment, teams prefer informal agile retrospectives, which involve no confined boundaries of time, venue, and participants.

关键词： Traditional Retrospective Informal Retrospective Team Retrospective Agile Retrospective Continuous Retrospective

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From Identities to Quantities: Introducing Items and Decoupling Points to Object-Centric Process Mining 5th

From Identities to Quantities: Introducing Items and Decoupl...

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5th International Conference on Process Mining (ICPM)

作者： Graves, Nina Koren, Istvan Rafiei, Majid van der Aalst, Wil M. P. Rhein Westfal TH Aachen Chair Proc & Data Sci PADS Aachen Germany

ISBN: (纸本)9783031561061;9783031561078

Logistics processes ensure that the right product is at the right location at the right time in the right quantity. Their efficiency is crucial to industrial operations, as they generate costs while not adding value to the product. Process mining techniques improve processes using real-life data. However, the application of process mining to logistics processes poses several challenges, as (1) recorded material movements refer to quantities of items, not individual objects and (2) the required data are often scattered over several systems requiring additional preprocessing efforts. This work presents the concept of item quantities to describe the movement of not individually identifiable items across distributed processes. Subsequently, we introduce a framework to integrate the explicit consideration of item quantities into process mining, consisting of a quantity-related event log and an extension of object-centric Petri nets as a basis for quantity-dependent process analysis. The analysis of an artificial event log demonstrates the additional insights the consideration of quantities uncovers and highlights the potential for the application of process mining in the logistics domain.

关键词： Process Mining Logistics Material Flow Analysis

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IPMD: Intentional Process Model Discovery from Event Logs 18th

IPMD: Intentional Process Model Discovery from Event Logs

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18th International Conference on Research Challenges in information Sciences (RCIS)

作者： Elali, Ramona Kornyshova, Elena Deneckere, Rebecca Salinesi, Camille Paris 1 Pantheon Sorbonne Paris France Conservatoire Natl Arts & Metiers Paris France

ISBN: (纸本)9783031594670;9783031594687

Intention Mining is a crucial aspect of understanding human behavior. It focuses on uncovering the underlying hidden intentions and goals that guide individuals in their activities. We propose the approach IPMD (Intentional Process Model Discovery) that combines Frequent Pattern Mining, Large Language Model, and Process Mining to construct intentional process models that capture the human strategies inherited from his decision-making and activity execution. This combination aims to identify recurrent sequences of actions revealing the strategies (recurring patterns of activities), that users commonly apply to fulfill their intentions. These patterns are used to construct an intentional process model that follows the MAP formalism based on strategy discovery.

关键词： Intention Mining Intentional Process Model Frequent Pattern Mining Process Mining Large Language Model

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A Tertiary Study on Quality in Use Evaluation of Smart Environment Applications 18th

A Tertiary Study on Quality in Use Evaluation of Smart Envir...

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18th International Conference on Research Challenges in information Sciences (RCIS)

作者： Angeloni, Maria Paula Correa Duque, Rafael de Oliveira, Kathia Marcal Grislin-Le Strugeon, Emmanuelle Tirnauca, Cristina UPHF CNRS UMR 8201 LAMIH Valenciennes France Univ Cantabria Dept Matemat Estadist & Computac Santander Spain INSA Hauts de France Valenciennes France

ISBN: (纸本)9783031594649;9783031594656

As the population grows older, the need for special assistance increases, and a modern alternative to mitigate the absence of face-to-face caregivers (which is expensive) is to take advantage of technological devices in so called smart environments, which can be an economical and practical solution. Guaranteeing the software quality of applications in these spaces before providing it to end users is essential, especially in situations involving senior citizens or people with motor disabilities. In order to investigate how the quality evaluation of smart environment applications has been performed, we carried out a tertiary study. From a total of 1,028 studies, 21 were carefully selected for analysis. The results confirmed that classical questionnaires and interviews are the techniques that are still used the most for evaluation, but that simulation appears as a new trend to that end.

关键词： Quality in Use Smart environments Literature review

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Precision-Guided Minimization of Arbitrary Declarative Process Models 25th

Precision-Guided Minimization of Arbitrary Declarative Proce...

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作者： Rocha, Eduardo Goulart van der Aalst, Wil M. P. Celonis Labs GmbH Munich Germany Rhein Westfal TH Aachen Proc & Data Sci PADS Chair Aachen Germany

ISBN: (纸本)9783031610066;9783031610073

Declarative model minimization is a computationally expensive task. State-of-the-art approximation techniques rely on hard-coded heuristic functions based on properties of constraint templates, which requires rework when new templates are added and cannot handle models expressed as arbitrary logical formulas. We present a precision-based heuristic function that requires no pre-configuration and can handle arbitrary constraints, provided they can be mapped to a finite automaton. The approach is evaluated on real-world datasets, where it outperforms state-of-the-art methods while accepting a wider range of inputs.

关键词： Process Mining Declarative Process Mining Constraint Minimization Redundant Constraints

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Robust Aggregation Function in Federated Learning 6th

Robust Aggregation Function in Federated Learning

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6th International Conference on information and Knowledge Systems (ICIKS)

作者： Taheri, Rahim Arabikhan, Farzad Gegov, Alexander Akbari, Negar Univ Portsmouth Sch Comp Portsmouth Hants England Univ Portsmouth Portsmouth Business Sch Portsmouth Hants England

ISBN: (纸本)9783031516634;9783031516641

Maintaining user data privacy is a crucial challenge for machine learning techniques. Federated learning is a solution that enables machine learning models to be trained using data residing on different devices without centralizing the data. This training method offers several advantages: Firstly, federated learning helps preserve user privacy by storing data on separate devices rather than transferring it to a central location for training. Secondly, training machine learning models on a diverse set of devices through federated learning improves their robustness, ensuring optimal performance in a wide range of real-world scenarios. Finally, federated learning can promote scalability by enabling simultaneous training on a vast number of devices. So, it can increase the scale of training and enable the development of more sophisticated models. The aggregation function is one of the main steps in federated learning and is used on the server side to aggregate local models sent from the client side. The most widely used aggregation function is Krum, which, despite the research done to improve its robustness, is still vulnerable to adversarial samples. In this paper, a method is proposed to improve the robustness of the Krum aggregation function. The results confirm that the proposed method is more robust against adversarial samples than the original version of the Krum aggregation function.

关键词： Federated Learning Robustness Krum Aggregation

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