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[null,"1.","Record Nr.",null,"UNINA9910886998303321"]
[null,null,"Autore",null,"Řepa Václav"]
[null,null,"Titolo",null,"Perspectives in Business Informatics Research : 23rd International Conference on Business Informatics Research, BIR 2024, Prague, Czech Republic, September 11–13, 2024, Proceedings / / edited by Václav Řepa, Raimundas Matulevičius, Emanuele Laurenzi"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024"]
[null,null,"ISBN",null,"3-031-71333-8"]
[null,null,"Edizione",null,"[1st ed. 2024.]"]
[null,null,"Descrizione fisica",null,"1 online resource (268 pages)"]
[null,null,"Collana",null,"Lecture Notes in Business Information Processing, , 1865-1356 ; ; 529"]
[null,null,"Disciplina",null,"005.3"]
[null,null,"Soggetti",null,"Information technology - Management"]
[{"$nulls":4},"Business information services"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Software engineering"]
[{"$nulls":4},"Computer Application in Administrative Data Processing"]
[{"$nulls":4},"IT in Business"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Enterprise Architecture"]
[{"$nulls":4},"Software Engineering"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Keynotes -- Democratization of AI Tools: Bridging the Gap between Business Informatics and Accessible AI Innovation -- A Meaningful Road to Explanation -- Contents -- AI Opportunities and Challenges -- Business, Data and Analytics: Specifying AI Use Cases with the Help of Modeling Techniques -- 1 Introduction -- 2 Case Study Setting and Related Requirements -- 2.1 Case Study Setting -- 2.2 Case Study Requirements -- 3 Related Work and Choice of the Conceptual Model -- 3.1 Business View -- 3.2 Data and Analytics View -- 4 Application in a Real-World Case Study -- 4.1 Business View by Top-Down Strategy -- 4.2 Business View by User-Centric Strategy -- 4.3 Data View for the Prediction of Annual Construction Costs -- 4.4 Analytics View for the Prediction of Annual Construction Costs -- 5 Usefulness and Practical Application Tips -- 5.1 Usefulness of the Conceptual Models -- 5.2 Efficient Use of the Conceptual Model -- 6 Conclusion -- References -- Generative "]
[{"$nulls":4},"AI for BPMN Process Analysis: Experiments with Multi-modal Process Representations -- 1 Introduction -- 2 Large Language Models and the BPM Lifecycle -- 3 Related Works -- 4 Experimental Setup -- 5 Experimental Outcomes and Evaluation -- 5.1 RDF vs. XML Formats -- 5.2 RDF vs. Images (PNG) -- 5.3 Future Work: Serialization Generation -- 6 Conclusions -- References -- LLM-Assistance for Quality Control of LLM Output -- 1 Introduction -- 2 Theoretical Background -- 2.1 Large Language Models -- 2.2 LLM Support for Enterprise Modelling -- 3 Related Work -- 3.1 Quality Evaluation of LLM Output -- 3.2 Literature Analysis on LLM for Quality Control in EM -- 4 Quality Criteria for LLM Output in EM -- 4.1 Definition of Quality Criteria -- 4.2 Operationalization of the Defined Criteria -- 5 Experiments into LLM for Quality Control of LLM in EM."]
[{"$nulls":4},"5.1 Experiments in Triangulation -- 5.2 Experiments in Inverse Mappings -- 6 Conclusion and Future Work -- References -- AI Applications and Use Cases in Business -- Unlocking Viewer Insights in Linear Television: A Machine Learning Approach -- 1 Introduction -- 2 Pipeline -- 2.1 Data Collection -- 2.2 Determining Viewer Time Slots -- 2.3 Content Genre Biases: Unveiling Viewer Preferences -- 2.4 Device Signature: Capturing Essential Features -- 2.5 Household Categorisation: Timing and Content -- 3 Data Analysis and Feature Selection -- 3.1 Classification Results -- 3.2 Feature Significance -- 4 Machine Learning Experiments and Results -- 4.1 Error Analysis: Confusion Matrices -- 4.2 Summary of Results -- 5 Related Works -- 6 Conclusions and Future Work -- References -- Comparison of AI-Based Document Classification Platforms -- 1 Introduction -- 2 Overview of the Field of Document Classification -- 3 Comparison Methodology -- 3.1 Description of the Dataset Used for the Study -- 3.2 Free Open Source Models Implementation -- 3.3 Overview of Proprietary Software -- 3.4 Evaluation Metrics and Methodology for Comparison -- 4 Results -- 4.1 Performance of Free Open Source Software -- 4.2 Performance of Proprietary Software -- 4.3 Cost Comparison -- 5 Discussion, Conclusion and Limitations -- References -- Towards Model-driven Enhancement of Safety in Healthcare Robot Interactions -- 1 Introduction -- 2 Background -- 2.1 Robots in Healthcare -- 2.2 Robot Interaction -- 2.3 Safety in Robot Interactions -- 2.4 Challenges and Shortcomings -- 2.5 Modeling -- 3 Methodology -- 4 Findings from the Literature Review -- 4.1 Faults -- 4.2 Safety Dimensions -- 4.3 Dependability -- 5 Elicited Requirements -- 6 Safety as a Modeling Viewpoint -- 7 Instantiation of the Meta-Model Slice for a Use Case -- 8 Discussion -- 9 Conclusions -- References -- Business Intelligence."]
[{"$nulls":4},"Modelling of Organisational Rules in Complex Adaptive Systems: a Systematic Mapping Study -- 1 Introduction -- 2 Organisations as Complex Adaptive Systems -- 3 Methodology -- 4 Results and Analysis -- 4.1 Components -- 4.2 Part-of -- 4.3 Behaviour -- 4.4 Adaptation -- 4.5 Complexity -- 5 Discussion -- 5.1 Abstraction and Power Relations -- 5.2 Absence of Nonlinearity and Nondeterminism -- 5.3 Social Interaction with Rules -- 5.4 Modelling Feedback Channels -- 6 Conclusion -- References -- Towards Method Support for Variability Modelling in Enterprise Architecture Management -- 1 Introduction -- 2 Research Approach -- 3 Background and Related Work -- 3.1 Enterprise Architecture Management -- 3.2 Variability in EAM -- 3.3 Method Engineering -- 4 Requirements to Method Support -- 4.1 Industrial Case Study -- 4.2 Method Requirements -- 5 Method Prototype -- 5.1 Definition of Building Block -- 5.2 Systematic Approach -- 5.3 Application of the Method Prototype in the Case Study -- 6 Discussion and Conclusions -- References -- Cross-section of Business Intelligence Projects: Information Systems Success "]
[{"$nulls":4},"Perspective -- 1 Introduction -- 2 Related Work -- 3 Business Intelligence Implementation Success Model -- 3.1 Foundation -- 3.2 Implementation Factors -- 3.3 Augmented Success Model -- 3.4 Project Success Evaluation -- 4 Implementation Projects -- 4.1 Successful Project Evaluation -- 4.2 Failed Project Evaluation -- 5 Conclusions -- References -- Business and Information Systems Development -- Incorporating Ethical Aspects in Information Systems Requirements Engineering -- 1 Introduction -- 2 Implementing Values into Requirements Engineering in Information Systems Context -- 2.1 Requirements Engineering -- 2.2 Ethical Analysis in Information Systems Research -- 3 Towards Introducing Ethical Analysis into Requirements Engineering -- 4 Discussion and Outlook."]
[{"$nulls":4},"References -- Suitability of Business Process Modeling Methods for Requirements Elicitation -- 1 Introduction -- 2 Background -- 2.1 On Requirements Engineering Standards -- 2.2 Business Process Modeling Languages and Methods -- 3 The Analysis of the Languages/Methods -- 4 Discussion -- 5 Conclusion -- References -- Software Architectures and the Use of Knowledge Graphs to Support Their Design -- 1 Introduction -- 2 Methodology -- 3 Related Works -- 4 The Knowledge Structures of MVC -- 5 Glueing Together UML Designs and TOGAF's Architecture Migration in a Knowledge Graph -- 6 Discussion on Generalization Potential -- 7 Conclusions -- References -- Technical Debt - Insights Into a Manufacturing SME Case Study -- 1 Introduction -- 2 Background -- 2.1 Technical Debt -- 2.2 Literature Review -- 3 Research Method and Data Collection -- 4 Results -- 4.1 Technical Debt Model -- 4.2 Comparison to Software Industry -- 5 Conclusion and Discussion -- References -- Knowledge and Traceability Management -- Discovery Rules for Depicting Tacit Knowledge Usage and Management in Fractal Enterprise Models -- 1 Introduction -- 2 Research Background -- 2.1 Tacit Knowledge -- 2.2 Introduction to Fractal Enterprise Model -- 2.3 Research Approach -- 2.4 Literature Review: Tacit Knowledge in Enterprise Models -- 2.5 Discovery Power of Enterprise Modeling Languages -- 3 Discovery Rules for Internal Tacit Assets Management -- 3.1 Adding Tacit Asset -- 3.2 Learning from Experience -- 3.3 Socialization -- 3.4 Externalization -- 3.5 Internalization -- 3.6 An Example -- 4 Discovery Rules for External Tacit Assets Management -- 5 Conclusion and Plans for the Future -- References -- DDIs-Graph: an Approach to Identify Drug-Drug Interactions and Recommend Alternative Drugs -- 1 Introduction -- 2 Background -- 3 Material and Methods -- 4 Approach -- 5 Validation -- 6 Conclusion."]
[{"$nulls":4},"References -- Exploring the Information Flow and the Grounding of Digital Product Passports Using the Work-Oriented Approach, an Industrial Case Study -- 1 Introduction -- 2 Background -- 2.1 Digital Product Passport -- 2.2 Work-Oriented Approach to Information Products (WOA) -- 3 Research and Case Method -- 3.1 Case Study Design -- 4 Industrial Case Study -- 4.1 Case Study Approach -- 4.2 WOA Starting Point -- 4.3 WOA Locate Context -- 4.4 WOA Frame -- 4.5 WOA Characterise -- 4.6 WOA Ground -- 4.7 WOA Retrospect -- 5 Discussions and Lessons Learned -- 6 Conclusions -- References -- Author Index."]
[null,null,null,"Sommario/riassunto","This book constitutes the proceedings of the 23rd International Conference on Perspectives in Business Informatics Research, BIR 2024, which took place in Prague, Czech Republic, in September 2024. The central theme of BIR 2024 was “Artificial Intelligence (AI) in Business Informatics: Opportunities and Challenges”. The 15 full papers and 1 short paper included in these proceedings were carefully reviewed and selected from 43 submissions. They cover different aspects of the "]
[{"$nulls":4},"discipline and are organized in sections on AI opportunities and challenges; AI applications and use cases in business; business intelligence; business and information systems development; and knowledge and traceability management."]