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

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Process-Specific Extensions for Enhanced Recommender Systems in business Process Management 1

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36th International Conference on Advanced information Systems Engineering (CAiSE)

作者： Petter, Sebastian Jablonski, Stefan Univ Bayreuth Bayreuth Germany

ISBN: (数字)9783031610035

ISBN: (纸本)9783031610028;9783031610035

In business Process Management (BPM) the integration of advanced recommender systems emerges as a critical strategy to enhance process efficiency and user satisfaction. Despite the dissemination of these systems, there remains a distinct lack of incorporating execution relevant context data, particularly those generated during process execution and prevailing environmental conditions. This paper addresses this gap by proposing process-specific extensions for augmenting an existing recommender system framework. Our approach not only enhances the adaptability and accuracy of recommendations but also sustains the applicability of existing algorithms, ensuring seamless integration into available recommender frameworks. The potential of this refined approach is demonstrated by evaluating a process scenario based on synthetic data.

关键词： business process management Recommender systems User-centered process improvement

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Implementing Object-Centric Event Data Models in Event Knowledge Graphs 5th

Implementing Object-Centric Event Data Models in Event Knowl...

引用

5th International Conference on Process Mining (ICPM)

作者： Swevels, Ava Fahland, Dirk Montali, Marco Eindhoven Univ Technol Eindhoven Netherlands Free Univ Bozen Bolzano Bolzano Italy

ISBN: (纸本)9783031561061;9783031561078

Recent advances in object-centric process mining necessitated the standardization of object-centric event data (OCED). An IEEE taskforce has developed a "meta-model" for OCED, but there is no existing reference implementation or automated techniques to transform legacy data into OCED. This task requires domain-specific knowledge about the semantics of the legacy data in order to make explicit how events act on various inter-related data objects and their attributes. We propose a semantic header that defines how extracted legacy data maps to OCED concepts and the domain-specific reference ontology using PG-schema. We automatically translate the header into database queries to construct an event knowledge graph that is compliant with OCED and the domain ontology using a declarative extract-load-transform approach. The approach has been implemented and demonstrated on 7 real-life datasets, making it one of the first attempts to make OCED operational.

关键词： OCED Semantic Header Event Knowledge Graph PG-Schema ELT Framework

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Use of Artificial Intelligence in Occupational Health and Safety in Construction Industry: A Proposed Framework for Saudi Arabia 11th

Use of Artificial Intelligence in Occupational Health and Sa...

引用

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

作者： Khahro, Shabir Hussain Khahro, Qasim Hussain Prince Sultan Univ Coll Engn Dept Engn Management Riyadh Saudi Arabia Univ Tun Hussein Onn Malaysia Fac Civil Engn & Built Environm Jamilus Res Ctr Batu Pahat 86400 Johor Malaysia

ISBN: (纸本)9783031581120;9783031581137

Occupational accidents have always been very important for all industries due to its significant impacts on projects and society. Whereas the case in construction industry is also similar due to higher number of occupational accidents recorded in various countries. In current dynamic technological era, conventional Health and Safety (H&S) practices are not sufficient thus new approaches are important to explore. It is observed from the detailed literature review that there are various existing tools designed by various researcher in different scenario but there is a lack to device an integrated approach. Therefore, this paper proposes an integrated approach to monitor the H&S at site. The proposed framework will help the decision makers to manage and monitor the health and safety practices at site in a real time environment.

关键词： Construction Safety Artificial Intelligence Big Data Worker Health Future Technologies

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A Conceptual Model of Digital Immune System to Increase the Resilience of Technology Ecosystems 18th

A Conceptual Model of Digital Immune System to Increase the ...

引用

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

作者： Krauze, Beate Grabis, Janis Riga Tech Univ 6A Kipsalas St LV-1048 Riga Latvia

ISBN: (纸本)9783031594649;9783031594656

In the light of technological advancements, disruptions and regulatory changes, various guidelines and standards emphasize the need for technology resilience. However, they often lack explicit evaluation methods, leaving organizations to determine their own implementation and assessment approaches. This absence of specific guidance amplifies the challenges organizations face in ensuring business continuity when critical systems fail. To address this, a "digital immune system" is proposed - a holistic approach to safeguard digital assets and mitigate IT-related risks. Digital immune system integrates processes, analytics and technologies to strengthen IT architecture, business operations and incorporates assessments to evaluate technology ecosystem resilience. Despite the acknowledged need for technology resilience, existing frameworks fall short in providing practical evaluation methods for the digital immune system. This paper confronts this challenge by focusing on the interconnected components of technologies, data and processes, considering emerging threats and compliance requirements. The goal of the research is to design an assessment framework for the digital immune system and establish a Digital Immune System Maturity Model. The model offers a structured path for organizations to measure and improve their IT risk assessment, resilience and business continuity plans.

关键词： Digital Immune System Resilience business Continuity Planning IT Risk Management

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ML-Enabled Systems Model Deployment and Monitoring: Status Quo and Problems 16th

ML-Enabled Systems Model Deployment and Monitoring: Status Q...

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16th Software Quality Days Conference (SWQD)

作者： Zimelewicz, Eduardo Kalinowski, Marcos Mendez, Daniel Giray, Gorkem Alves, Antonio Pedro Santos Lavesson, Niklas Azevedo, Kelly Villamizar, Hugo Escovedo, Tatiana Lopes, Helio Biffl, Stefan Musil, Juergen Felderer, Michael Wagner, Stefan Baldassarre, Teresa Gorschek, Tony Pontif Catholic Univ Rio De Janeiro PUC Rio Rio De Janeiro Brazil Blekinge Inst Technol BTH Karlskrona Sweden Vienna Univ Technol TU Wien Vienna Austria German Aerosp Ctr DLR Cologne Germany Univ Cologne Cologne Germany Tech Univ Munich Munich Germany Univ Bari Bari Italy Fortiss GmbH Munich Germany

ISBN: (纸本)9783031562808;9783031562815

[Context] Systems that incorporate Machine Learning (ML) models, often referred to as ML-enabled systems, have become commonplace. However, empirical evidence on how ML-enabled systems are engineered in practice is still limited;this is especially true for activities surrounding ML model dissemination. [Goal] We investigate contemporary industrial practices and problems related to ML model dissemination, focusing on the model deployment and the monitoring ML life cycle phases. [Method] We conducted an international survey to gather practitioner insights on how ML-enabled systems are engineered. We gathered a total of 188 complete responses from 25 countries. We analyze the status quo and problems reported for the model deployment and monitoring phases. We analyzed contemporary practices using bootstrapping with confidence intervals and conducted qualitative analyses on the reported problems applying open and axial coding procedures. [Results] Practitioners perceive the model deployment and monitoring phases as relevant and difficult. With respect to model deployment, models are typically deployed as separate services, with limited adoption of MLOps principles. Reported problems include difficulties in designing the architecture of the infrastructure for production deployment and legacy application integration. Concerning model monitoring, many models in production are not monitored. The main monitored aspects are inputs, outputs, and decisions. Reported problems involve the absence of monitoring practices, the need to create custom monitoring tools, and the selection of suitable metrics. [Conclusion] Our results help provide a better understanding of the adopted practices and problems in practice and support guiding ML deployment and monitoring research in a problem-driven manner.

关键词： Machine Learning Deployment Monitoring

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Identifying Relevant Data in RDF Sources 18th

Identifying Relevant Data in RDF Sources

引用

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

作者： Chevallier, Zoe Kedad, Zoubida Finance, Beatrice Chaillan, Frederic Univ Versailles Paris Saclay DAVID Lab Versailles France Grand Paris Sud Evry France

ISBN: (纸本)9783031594670;9783031594687

The increasing number of RDF data sources published on the web represents an unprecedented amount of information. However, querying these sources to extract the relevant information for a specific need represented by a target schema is a complex task as the alignment between the target and the source schemas might not be provided or incomplete. This paper presents an approach which aims at automatically populating the classes of a target schema. Our approach relies on a semi-supervised learning algorithm that iteratively identifies instance patterns in the data source that represent candidate instances for the target schema. We present some preliminary experiments showing the effectiveness of our approach.

关键词： RDF data sources Target Schema Instantiation Web Data extraction Semi-supervised learning

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Selection of Rapid Classifier Development Methodology Used to Implement a Screening Study Based on Children's Behavior During School Lessons 24th

Selection of Rapid Classifier Development Methodology Used t...

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24th International Conference on Group Decision and Negotiation (GDN)

作者： Dziczkowski, Grzegorz Jach, Tomasz Probierz, Barbara Stefanski, Piotr Kozak, Jan Univ Econ Katowice Dept Machine Learning 1 Maja 50 PL-40287 Katowice Poland Inst Innovat Technol EMAG Lukasiewicz Res Network Leopolda 31 PL-40189 Katowice Poland

ISBN: (纸本)9783031593727;9783031593734

The purpose of the article is to prepare a methodology for an advanced system that implements screening among children of early school age. The screening will be implemented in classrooms using cameras. Cameras in bi-weekly windows will study children's behavior and the system will report alerts when abnormal behavior is detected. The alerts are intended to recommend in-depth examinations with a specialist. In this article, the authors present a preliminary study to assess the feasibility of rapidly creating classifiers that detect specific behavioral elements (e.g., open mouth, putting fingers in mouth, asymmetrical closing of eyes, etc.). The article aims to define a methodology for detecting anomalies in children's behavior, which in the next stages of the project will be used to detect undesirable behaviors such as lack of concentration, hyperactivity, epilepsy, undesirable behavior to noise and stress. The aim of the presented research is to create a methodology based on proprietary neural network-based classifiers in later studies implementing screening tests. The presented article presents research comparing the performance of two different neural network architectures: an advanced ResNet-based model and a simpler custom convolutional neural network (CNN). The research presented here demonstrates that both advanced and simple models have their place in the rapid development of microclassifiers and allow acceptance of the chosen methodology for further work on student screening.

关键词： Computer Vision Behavior analysis machine learning knowledge discovery in databases

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Analyzing an After-Sales Service Process Using Object-Centric Process Mining: A Case Study 5th

Analyzing an After-Sales Service Process Using Object-Centri...

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5th International Conference on Process Mining (ICPM)

作者： Park, Gyunam Aydin, Sevde Ugur, Cuneyt van der Aalst, Wil M. P. Rhein Westfal TH Aachen Proc & Data Sci Grp PADS Aachen Germany Gebze Tech Univ Darica Turkiye Borusan Cat R&D Digital & Technol AI & Proc Automat Dept Darica Turkiye

ISBN: (纸本)9783031561061;9783031561078

Process mining, a technique turning event data into business process insights, has traditionally operated on the assumption that each event corresponds to a singular case or object. However, many real-world processes are intertwined with multiple objects, making them object-centric. This paper focuses on the emerging domain of object-centric process mining, highlighting its potential yet underexplored benefits in actual operational scenarios. Through an in-depth case study of Borusan Cat's after-sales service process, this study emphasizes the capability of object-centric process mining to capture entangled business process details. Utilizing an event log of approximately 65,000 events, our analysis underscores the importance of embracing this paradigm for richer business insights and enhanced operational improvements.

关键词： Object-Centric Process Mining Case Study After-Sales Service Process

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Empathy vs Reluctance to Challenge Misinformation: The Mediating Role of Relationship Costs, Perspective Taking, and Need for Cognition 18th

Empathy vs Reluctance to Challenge Misinformation: The Media...

引用

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

作者： Abumalloh, Rabab Ali Gurgun, Selin Noman, Muaadh Phalp, Keith Halabi, Osama Katos, Vasilis Ali, Raian Qatar Univ Dept Comp Sci & Engn Doha Qatar Bournemouth Univ Fac Sci & Technol Poole England Hamad Bin Khalifa Univ Coll Sci & Engn Doha Qatar

ISBN: (纸本)9783031594649;9783031594656

Misinformation can harm individuals and societies, with social media and online communities amplifying its reach and impact. One effective strategy to counteract the spread of misinformation online is social corrections, in which people on socialmedia actively challenge others who post or spread it. People hesitate to do so for reasons related to empathy, fear of affecting their relationships, futility, and subjective norms. This research aims to explore the impact of empathy on individuals' willingness to challenge misinformation. The research also investigates the mediation role of the personal factors of perspective-taking and the need for cognition, along with the perceived impacts on their relationships, on the relationship between empathy and the willingness to challenge. The data was collected from 250 UK-based social networking users and then analyzed using Partial Least Squares Structural Equation Modeling. The results of the analysis supported that perspective-taking ( beta = 0.064, p = 0.011), the need for cognition ( beta = 0.022, p = 0.048), and perceived relationship costs (beta = 0.035, p = 0.003) all fully mediated the impact of empathy on the willingness to challenge misinformation. The results also show that empathy does not have a direct impact on willingness to challenge misinformation. Individuals with varying levels of empathy converge in their attitudes toward challenging misinformation influenced by a combination of cognitive processes and considerations of their relationships.

关键词： Misinformation Social Correction Relationship Cost Empathy Perspective Taking Need for Cognition

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ExpO: Towards Explaining Ontology-Driven Conceptual Models 18th

ExpO: Towards Explaining Ontology-Driven Conceptual Models

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

作者： Romanenko, Elena Calvanese, Diego Guizzardi, Giancarlo Free Univ Bozen Bolzano Bolzano Italy Umea Univ Umea Sweden Univ Twente Enschede Netherlands Stockholm Univ Stockholm Sweden

ISBN: (纸本)9783031594670;9783031594687

Ontology-driven conceptual models play an explanatory role in complex and critical domains. However, since those models may consist of a large number of elements, including concepts, relations and sub-diagrams, their reuse or adaptation requires significant efforts. While conceptual model engineers tend to be biased against the removal of information from the models, general users struggle to fully understand them. The paper describes ExpO-a prototype that addresses this tradeoff by providing three components: (1) an API that implements model transformations, (2) a software plugin aimed at modelers working with the language OntoUML, and (3) a web application for model exploration mostly designed for domain experts. We describe characteristics of every component and specify scenarios of possible usages.

关键词： Ontology-Driven Conceptual Models OntoUML Pragmatic explanation Software Tools

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