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001 2210080935179
003 DE-He213
005 20250321105505
007 cr nn 008mamaa
008 241026s2025 sz | s |||| 0|eng d
020 a97830317559969978-3-031-75599-6
024 a10.1007/978-3-031-75599-62doi
040 a221008
050 aQA76.758
072 aUMZ2bicssc
072 aCOM0512302bisacsh
072 aUMZ2thema
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245 00 aAdvances in Conceptual Modelingh[electronic resource] :bER 2024 Workshops, AISA, CMLS, EmpER, QUAMES, JUSMOD, LLM4Modeling, Pittsburgh, PA, USA, October 28–31, 2024, Proceedings /cedited by Motoshi Saeki, Leah Wong, João Araujo, Clara Ayora, Anna Bernasconi, Matteo Buffa, Silvana Castano, Peter Fettke, Hans-Georg Fill, Alberto García S., Miguel Goulão, Cristine Griffo, Jin-Taek Jung, Julius Köpke, Beatriz Marín, Stefano Montanelli, Edelweis Rohrer, José F. Reyes Román.
250 a1st ed. 2025.
264 aCham :bSpringer Nature Switzerland :bImprint: Springer,c2025.
300 aXIX, 378 p. 108 illus., 79 illus. in color.bonline resource.
336 atextbtxt2rdacontent
337 acomputerbc2rdamedia
338 aonline resourcebcr2rdacarrier
347 atext filebPDF2rda
490 aLecture Notes in Computer Science,x1611-3349 ;v14932
505 aAISA -- The First International Workshop on AI Services and Applications -- Empirical case study of AI Service and Application for people with disabilities -- A Methodological Framework for Designing Human Centered Artificial Intelligence Services -- Beyond One Fits All A Case Study Approach to AI System Design Methods -- GRASPER Leveraging Knowledge Graphs for Predictive Supply Chain Analytics -- An MLOps Framework to Data Driven Modelling of Digital Twins with an Application to Virtual Test Rigs -- Empirical Study on the Use of Artificial General Intelligence Healthcare in the Elderly -- Effects of Perceived Ease of Use and Perceived Usefulness of Technology Acceptance Model on Intention to Continue Using Generative AI Focusing on the Mediating Effect of Satisfaction and Moderating Effect of Innovation Resistance -- Conceptual Modeling for Public AI Systems -- Self-Explanatory Retrieval Augmented Generation for SDG Evidence Identification -- CMLS -- International Workshop on Conceptual Modeling for Life Sciences CMLS -- On the Expressiveness of Petri Nets for Modeling Biological Processes the Case for mRNA Translation and Protein Synthesis -- Enhancing Vaxign DL for Vaccine Candidate Prediction with added ESM Generated Features -- Conceptual Modeling for Polygenic Risk Score Research Improving Domain Understanding and Clinical Utility -- Integrative Ontology of Bipolar Disorder OBD Advancing Bipolar Disorder Research through an Interoperable Ontological Framework -- EmpER -- 7th International Workshop on Empirical Methods in Conceptual Modeling EmpER’24 -- How Does UML Look and Sound Using AI to Interpret UML Diagrams through Multimodal Evidence -- Can Large Language Models Learn Conceptual Modeling by Looking at Slide Decks and Pass Graduate Examinations An Empirical Study -- Evaluating a Framework of Conceptual Modelling Research -- Extending Goal Models with Execution Orders An Investigation of the Impact on Comprehensibility -- QUAMES -- 5th International Workshop on Quality and Measurement of Model-Driven Software Development QUAMES 2024 -- Towards leveraging gamified code testing for effective model validation -- JUSMOD -- 3rd International Workshop on Digital JUStice digital law and conceptual MODeling JUSMOD24 -- Resignifying Compliance between Ontologies and Epistemologies of Law -- Modelling Legal Enforcement with UFOL a Case from Swedish Healthcare -- The eu FAIRnews A Preliminary Exploration of Bridging Disinformation and Digital Justice through FAIR Data Practices in Online News Sources -- Safety Assurances in Autonomous Vessels -- LLM4Modeling -- 2nd Workshop ”Modeling in the Age of Large Language Models” LLM4Modeling -- An LLM Assistant for Characterizing Conceptual Modeling Research Contributions -- AI Assisted Analytics An Automated Approach to Data Visualization -- Combining Natural Language Generation and Graph Algorithms to Explain Causal Maps through Meaningful Paragraphs.
520 aThis book constitutes the refereed proceedings of the workshops held at the 43rd International Conference on Conceptual Modeling, ER 2024, which took place in Pittsburgh, PA, USA, during October 28-31, 2024. The 22 full papers and 1 short paper included in this book were carefully reviewed and selected from 52 submissions. They stem from the following workshops: AISA’2024 - The First International Workshop on AI Services and Applications CMLS2024 - The 5th International Workshop on Conceptual Modeling for Life Sciences EmpER'24 -7th International Workshop on Empirical Methods in Conceptual Modeling QUAMES 2024 - 5th International Workshop on Quality and Measurement of Model-Driven Software Development JUSMOD24 - 3rd International Workshop on Digital JUStice, Digital Law and Conceptual MODeling LLM4Modeling - 2nd Workshop on Modeling in the Age of Large Language Models.
650 aSoftware engineering.
650 aApplication software.
650 aData structures (Computer science).
650 aInformation theory.
650 aArtificial intelligence.
650 aComputer networks .
650 aInformation technologyxManagement.
650 aSoftware Engineering.
650 aComputer and Information Systems Applications.
650 aData Structures and Information Theory.
650 aArtificial Intelligence.
650 aComputer Communication Networks.
650 aComputer Application in Administrative Data Processing.
700 aSaeki, Motoshi.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt
700 aWong, Leah.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt
700 aAraujo, João.eeditor.0(orcid)0000-0001-5914-16311https://orcid.org/0000-0001-5914-16314edt4http://id.loc.gov/vocabulary/relators/edt
700 aAyora, Clara.eeditor.0(orcid)0009-0002-8265-65311https://orcid.org/0009-0002-8265-65314edt4http://id.loc.gov/vocabulary/relators/edt
700 aBernasconi, Anna.eeditor.0(orcid)0000-0001-8016-57501https://orcid.org/0000-0001-8016-57504edt4http://id.loc.gov/vocabulary/relators/edt
700 aBuffa, Matteo.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt
700 aCastano, Silvana.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt
700 aFettke, Peter.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt
700 aFill, Hans-Georg.eeditor.0(orcid)0000-0001-5076-53411https://orcid.org/0000-0001-5076-53414edt4http://id.loc.gov/vocabulary/relators/edt
700 aGarcía S., Alberto.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt
700 aGoulão, Miguel.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt
700 aGriffo, Cristine.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt
700 aJung, Jin-Taek.eeditor.0(orcid)0009-0002-4674-54301https://orcid.org/0009-0002-4674-54304edt4http://id.loc.gov/vocabulary/relators/edt
700 aKöpke, Julius.eeditor.0(orcid)0000-0002-6678-57311https://orcid.org/0000-0002-6678-57314edt4http://id.loc.gov/vocabulary/relators/edt
700 aMarín, Beatriz.eeditor.0(orcid)0000-0001-8025-00231https://orcid.org/0000-0001-8025-00234edt4http://id.loc.gov/vocabulary/relators/edt
700 aMontanelli, Stefano.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt
700 aRohrer, Edelweis.eeditor.0(orcid)0000-0002-8257-52911https://orcid.org/0000-0002-8257-52914edt4http://id.loc.gov/vocabulary/relators/edt
700 aRomán, José F. Reyes.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt
710 aSpringerLink (Online service)
773 tSpringer Nature eBook
776 iPrinted edition:z9783031755989
776 iPrinted edition:z9783031756009
830 aLecture Notes in Computer Science,x1611-3349 ;v14932
856 uhttps://doi.org/10.1007/978-3-031-75599-6
912 aZDB-2-SCS
912 aZDB-2-SXCS
912 aZDB-2-LNC
950 aComputer Science (SpringerNature-11645)
950 aComputer Science (R0) (SpringerNature-43710)
Advances in Conceptual Modeling[electronic resource] :ER 2024 Workshops, AISA, CMLS, EmpER, QUAMES, JUSMOD, LLM4Modeling, Pittsburgh, PA, USA, October 28–31, 2024, Proceedings /edited by Motoshi Saeki, Leah Wong, João Araujo, Clara Ayora, Anna Bernasconi, Matteo Buffa, Silvana Castano, Peter Fettke, Hans-Georg Fill, Alberto García S., Miguel Goulão, Cristine Griffo, Jin-Taek Jung, Julius Köpke, Beatriz Marín, Stefano Montanelli, Edelweis Rohrer, José F. Reyes Román
Material type
전자책
Title
Advances in Conceptual Modeling[electronic resource] :ER 2024 Workshops, AISA, CMLS, EmpER, QUAMES, JUSMOD, LLM4Modeling, Pittsburgh, PA, USA, October 28–31, 2024, Proceedings /edited by Motoshi Saeki, Leah Wong, João Araujo, Clara Ayora, Anna Bernasconi, Matteo Buffa, Silvana Castano, Peter Fettke, Hans-Georg Fill, Alberto García S., Miguel Goulão, Cristine Griffo, Jin-Taek Jung, Julius Köpke, Beatriz Marín, Stefano Montanelli, Edelweis Rohrer, José F. Reyes Román
판 사항
1st ed. 2025.
Physical Description
XIX, 378 p 108 illus, 79 illus in color online resource.
Keyword
This book constitutes the refereed proceedings of the workshops held at the 43rd International Conference on Conceptual Modeling, ER 2024, which took place in Pittsburgh, PA, USA, during October 28-31, 2024. The 22 full papers and 1 short paper included in this book were carefully reviewed and selected from 52 submissions. They stem from the following workshops: AISA’2024 - The First International Workshop on AI Services and Applications CMLS2024 - The 5th International Workshop on Conceptual Modeling for Life Sciences EmpER'24 -7th International Workshop on Empirical Methods in Conceptual Modeling QUAMES 2024 - 5th International Workshop on Quality and Measurement of Model-Driven Software Development JUSMOD24 - 3rd International Workshop on Digital JUStice, Digital Law and Conceptual MODeling LLM4Modeling - 2nd Workshop on Modeling in the Age of Large Language Models.
내용주기
AISA / The First International Workshop on AI Services and Applications / Empirical case study of AI Service and Application for people with disabilities / A Methodological Framework for Designing Human Centered Artificial Intelligence Services / Beyond One Fits All A Case Study Approach to AI System Design Methods / GRASPER Leveraging Knowledge Graphs for Predictive Supply Chain Analytics / An MLOps Framework to Data Driven Modelling of Digital Twins with an Application to Virtual Test Rigs / Empirical Study on the Use of Artificial General Intelligence Healthcare in the Elderly / Effects of Perceived Ease of Use and Perceived Usefulness of Technology Acceptance Model on Intention to Continue Using Generative AI Focusing on the Mediating Effect of Satisfaction and Moderating Effect of Innovation Resistance / Conceptual Modeling for Public AI Systems / Self-Explanatory Retrieval Augmented Generation for SDG Evidence Identification / CMLS / International Workshop on Conceptual Modeling for Life Sciences CMLS / On the Expressiveness of Petri Nets for Modeling Biological Processes the Case for mRNA Translation and Protein Synthesis / Enhancing Vaxign DL for Vaccine Candidate Prediction with added ESM Generated Features / Conceptual Modeling for Polygenic Risk Score Research Improving Domain Understanding and Clinical Utility / Integrative Ontology of Bipolar Disorder OBD Advancing Bipolar Disorder Research through an Interoperable Ontological Framework / EmpER / 7th International Workshop on Empirical Methods in Conceptual Modeling EmpER’24 / How Does UML Look and Sound Using AI to Interpret UML Diagrams through Multimodal Evidence / Can Large Language Models Learn Conceptual Modeling by Looking at Slide Decks and Pass Graduate Examinations An Empirical Study / Evaluating a Framework of Conceptual Modelling Research / Extending Goal Models with Execution Orders An Investigation of the Impact on Comprehensibility / QUAMES / 5th International Workshop on Quality and Measurement of Model-Driven Software Development QUAMES 2024 / Towards leveraging gamified code testing for effective model validation / JUSMOD / 3rd International Workshop on Digital JUStice digital law and conceptual MODeling JUSMOD24 / Resignifying Compliance between Ontologies and Epistemologies of Law / Modelling Legal Enforcement with UFOL a Case from Swedish Healthcare / The eu FAIRnews A Preliminary Exploration of Bridging Disinformation and Digital Justice through FAIR Data Practices in Online News Sources / Safety Assurances in Autonomous Vessels / LLM4Modeling / 2nd Workshop ”Modeling in the Age of Large Language Models” LLM4Modeling / An LLM Assistant for Characterizing Conceptual Modeling Research Contributions / AI Assisted Analytics An Automated Approach to Data Visualization / Combining Natural Language Generation and Graph Algorithms to Explain Causal Maps through Meaningful Paragraphs.
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