{"id":948,"date":"2026-04-17T13:11:47","date_gmt":"2026-04-17T13:11:47","guid":{"rendered":"https:\/\/caise26.polimi.it\/?page_id=948"},"modified":"2026-04-24T13:44:13","modified_gmt":"2026-04-24T13:44:13","slug":"accepted-papers","status":"publish","type":"page","link":"https:\/\/caise26.polimi.it\/?page_id=948","title":{"rendered":"Accepted Papers"},"content":{"rendered":"

\"\"\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/p>\n

Accepted Papers<\/strong><\/h2>\n

Main conference<\/h2>\n

Enterprise Intelligence, Complexity, and Decision Support<\/h4>\n
    \n
  • M. Schnellmann, H. A. Proper, From Gut Feeling to Data-Driven Decisions: Exploring Digital Twin supported Decision-Making for Real Estate Management<\/i><\/li>\n
  • J. L. R. Moreira, E. Stoica, J. P. S. Piest, F. Bukhsh, W. Levelt, A Measurement Method for Quantifying Application Landscape Complexity with Enterprise Architecture<\/i><\/li>\n
  • F. J. Cavero, A. Garc\u00eda-Fern\u00e1ndez, J. A. Parejo, M. Resinas, A. Ruiz-Cort\u00e9s, Pricing Intelligence: Rethinking IS Engineering in Volatile SaaS Environments<\/i><\/li>\n<\/ul>\n

    Forecasting, Drift, and Prescriptive Process Analytics<\/h4>\n
      \n
    • B. R. A. Zuniga, A. Yeshchenko, H. van der Aa, Version Clustering: A Top-Down Approach for Process Concept Drift Detection<\/i><\/li>\n
    • Y. Yu, J. Peeperkorn, J. De Smedt, J. De Weerdt, Time Series Foundation Models for Process Model Forecasting<\/i><\/li>\n
    • N.-D. Le, A. Buliga, M. Ronzani, A. Padella, M. de Leoni, Balancing KPIs through Multi-Objective Prescriptive Process Analytics<\/i><\/li>\n<\/ul>\n

      Conceptual Modeling, Ontologies, and Value<\/h4>\n
        \n
      • I. Valle, T. P. Sales, E. Guerra, L. O. B. da Silva Santos, H. Proper, G. Guizzardi, Modeling Value Canvas: A tool to rationalize the value of domain modeling<\/i><\/li>\n
      • W. Morlidge, E. Watkiss-Leek, G. Hannah, H. Rostron, A. Ng, E. Johnson, A. Mitchell, T. R. Payne, V. Tamma, J. de Berardinis, The AnIML Ontology: Enabling Semantic Interoperability for Large-Scale Experimental Data in Interconnected Scientific Labs<\/i><\/li>\n
      • Y. Wuwang, N. Kannengie\u00dfer, T. Dehling, B. Sturm, A. Sunyaev, Decentralization drivers for purposeful decentralization of distributed ledger technology systems<\/i><\/li>\n<\/ul>\n

        Enriching Process Mining with Context and Sustainability<\/h4>\n
          \n
        • A. Moradbeikie, I. M. Grigore, S. I. Lopes, S. Barbon Junior, Sensor2EventLog: Bridging Continuous IoT Data and Process Mining through Eventization<\/i><\/li>\n
        • A. Swevels, F. Zerbato, D. Fahland, Process Mining in Context: Extending Domain Data Models for Iterative Analysis<\/i><\/li>\n
        • N. Wolf, H. Wittges, S. Rinderle-Ma, SuXXES: Integrating Sustainability Data into Process Event Logs<\/i><\/li>\n<\/ul>\n

          Human-in-the-Loop Engineering and Development Practices<\/h4>\n
            \n
          • C. Sancricca, C. Cesana, E. Gallo, A. Gottardi, C. Cappiello, How Poor Data Quality Weakens the Performance of Question\u2013Answering Systems<\/i><\/li>\n
          • S. Surana, A. Srinivasan, M. Bain, Engineering Systems for Data Analysis Using Interactive Structured Inductive Programming<\/i><\/li>\n
          • D. Ly, F. B. Aydemir, F. Dalpiaz, From Concept to Action: How Do Agile Software Teams Decompose User Stories into Tasks?<\/i><\/li>\n<\/ul>\n

            Process Discovery and Analysis<\/h4>\n
              \n
            • P. Schalk, A. Polyvyanyy, Mind the Gap: On Formal Relationships Between Log Complexity and the Complexity of Discovered Models<\/i><\/li>\n
            • T.-H. Huang, L. Jansen, M. Pegoraro, G. Park, W. van der Aalst, Flexible and Hierarchical Decomposition of Workflow Nets for Process Analysis<\/i><\/li>\n
            • A. Karunaratne, A. Polyvyanyy, A. Moffat, Conditioning and Stability in Process Discovery<\/i><\/li>\n<\/ul>\n

              Engineering AI Systems across Cloud, Edge, and Cyber-Physical Environments<\/h4>\n
                \n
              • A. Puglisi, F. Monti, F. Leotta, C. Napoli, M. Mecella, SlimAI4Edge: A cloud-edge framework for downsizing AI models as-a-service<\/i><\/li>\n
              • D. Zyberaj, L. Mazur, P. Hirmer, N. Petrovic, M. Aiello, Req2Road: A GenAI Pipeline for SDV Test Artifact Generation and On-Vehicle Execution<\/i><\/li>\n
              • A. Hassan, M. S. Saeed, B. Senouci, B. Benatallah, Domain-Specific Fine-Tuning of Large Language Models for HW\/SW Interface Generation: An Empirical Study<\/i><\/li>\n
              • H. Stein, S. Janzen, C. K. Agnes, D. T. Ninh, W. Maass, Towards Decision Support Systems for Cost-effective and Energy-efficient AI Operations in Data Centers<\/i><\/li>\n<\/ul>\n

                LLM-Driven Modeling and Human\u2013AI Collaboration<\/h4>\n
                  \n
                • I. Reinhartz-Berger, A. Tsoury, Iterative vs. Plan-Driven Approaches in LLM-Assisted Modeling: An Empirical Study<\/i><\/li>\n
                • J. Zdravkovic, J. Stirna, C. H. Tsai, K. Sandkuhl, An AI Enterprise Modeling Project Assistant \u2013 Needs and Possibilities<\/i><\/li>\n
                • S. J. Ali, Z. Zheng, D. Bork, Shortcut or Understanding? Diagnosing LLM Type Prediction in Conceptual Models<\/i><\/li>\n
                • Y. J. Chung, K. Bae, E. Yu, Modeling and Analyzing Identity-Sensitive Requirements in Human-AI Collaboration<\/i><\/li>\n<\/ul>\n

                  Agent-Based and Multi-Stakeholder Process Interaction<\/h4>\n
                    \n
                  • A. Ghasemi, L. Kulms, T. Lichtenstein, M. Weske, Agent-Based Simulation of Flexible Process Interactions<\/i><\/li>\n
                  • Q. Shen, A. Polyvyanyy, N. Lipovetzky, T. Kampik, Mining Agent Roles from Event Data for Effective Process Simulation<\/i><\/li>\n
                  • V. Pant, E. Yu, Computational Foundations for Strategic Coopetition: Bridging Conceptual Modeling and Game Theory in Multi-Stakeholder Information Systems<\/i><\/li>\n<\/ul>\n

                    LLMs and AI for Process Understanding<\/h4>\n
                      \n
                    • T. Sulzer, H. Voelzer, B. Weber, Evaluation of an Architecture for an LLM-based Analytics System for Exploratory Process Mining<\/i><\/li>\n
                    • J. Neuberger, H. van der Aa, H. Lopez, I. Khrop, Enabling Small Language Models for Text-to-Process Extraction: Balancing Accuracy and Efficiency through Distant Supervision<\/i><\/li>\n
                    • W. Zhang, K. Andree, A. Kalenkova, L. Pufahl, L. Mitchell, Explaining ML-Based Decision Models Through Process Mining Techniques<\/i><\/li>\n<\/ul>\n

                      Predictive and Neuro-Symbolic Process Analytics<\/h4>\n
                        \n
                      • H. Mustroph, M. Kunkler, S. Rinderle-Ma, Predicting Conformance Deviations and Their Positions in Future Event Sequences<\/i><\/li>\n
                      • J. Wang, K. Chen, C. Hou, T. Li, L. Lin, B. Cao, J. Fan, A Heterogeneous Hypergraph-Transformer Hybrid Architecture for Business Process Next-Activity Prediction<\/i><\/li>\n
                      • F. De Santis, G. Park, W. M. P. van der Aalst, F. Zanichelli, Compliance-Aware Predictive Process Monitoring: A Neuro-Symbolic Approach<\/i><\/li>\n
                      • D. Gaikwad, G. Park, W. van der Aalst, Neuro-Symbolic Process Anomaly Detection<\/i><\/li>\n<\/ul>\n

                        Responsible, Fair, and Human-Centered AI<\/h4>\n
                          \n
                        • L. Djennane, Z. Kardkovacs, B. Benatallah, Y. Gaci, Z. Farah, Proxy Analysis in Bias Testing<\/i><\/li>\n
                        • O. Diaz, X. Garmendia, R. Medeiros, STAR: A Socio-Technical Readiness Model for Assessing Task Readiness for AI Augmentation<\/i><\/li>\n
                        • M. Fumagalli, S. M. Nicoletti, D. Calvanese, G. Guizzardi, News-Informed Probabilistic Models for AI Risk Analysis<\/i><\/li>\n
                        • M. Peixoto, F. Bai\u00e3o, R. Guizzardi, G. Guizzardi, Explaining and Mitigating Biased Decisions: An Ontological Approach<\/i><\/li>\n<\/ul>\n

                          Object-Centric Process Mining and Conformance<\/h4>\n
                            \n
                          • L. Liss, W. van der Aalst, Object-Centric Conformance Checking on Object-Centric Causal Nets<\/i><\/li>\n
                          • H. Hooshyar, M. Fumagalli, M. Montali, G. Guizzardi, Time and Relations into Focus: Ontological Foundations of Object-Centric Event Data<\/i><\/li>\n
                          • M. Basmer, R.-D. Falcusan, M. Montali, M. Weidlich, Porifera: A Relational Approach to Conformance Checking for Object-Centric Behavioral Constraints<\/i><\/li>\n<\/ul>\n

                            Process Mining Data Quality and Repair<\/h4>\n
                              \n
                            • S. Kalukapuge, A. Janusz, M. T. Wynn, DupliMend: Online Detection and Refinement of Imprecise Activity Labels<\/i><\/li>\n
                            • M. Comuzzi, S. Ra, D. Narmatova, S. Cho, Y. Hong, S. Jung, Towards Agentic AI for Event Log Quality Assessment<\/i><\/li>\n
                            • S. Dissegna, C. Di Francescomarino, M. Ronzani, Graph-based Event Log Repair<\/i><\/li>\n<\/ul>\n

                              Forum and demo track<\/h2>\n

                              Vision papers<\/h4>\n
                                \n
                              • S. Hacks, Train While You Fight – Technical Requirements for Advanced Distributed Learning Platforms<\/i><\/li>\n
                              • J. Akoka, I. Comyn-Wattiau, C. Du Mouza, Automated Extraction of Conceptual Representations from Research Articles Using Large Language Models<\/i><\/li>\n
                              • V. G. dos Santos, B. Benatallah, S. T. MacMahon, Constraint-Aware Pipeline for Generating High-Quality Utterances from OpenAPI Specifications using LLMs<\/i><\/li>\n
                              • R. Grati, N. Fattouch, K. Boukadi, F. De Luzi, M. Mecella, A. Saffeh, A case study of eXplainable AI in smart agriculture. Lessons learned for information systems engineers<\/i><\/li>\n
                              • K. Saxena, B. Sarmah, S. Pasquali, ProvenanceTrace: Atomic Claim Verification Across Financial and Open-Domain AI Systems<\/i><\/li>\n
                              • D. Xhani, J. L. R. Moreira, M. van Sinderen, L. F. Pires, G. Guizzardi, M. Machado, Towards a FAIR Data Management Framework for Ontology-Driven Explainable Machine Learning<\/i><\/li>\n
                              • C. Capit\u00e1n-Agudo, C. Di Ciccio, C. Cabanillas, M. Resinas, Towards Explaining Process Variants With Examples<\/i><\/li>\n
                              • A. Bagozi, D. Bianchini, M. Garda, M. Melchiori, A. Rula, OntoLLM: A Framework for Trustworthy LLM Pipelines<\/i><\/li>\n
                              • J. C. Orth, A. Palma, M. Angelini, Towards Human-AI Collaborative Cybersecurity Compliance Assessment<\/i><\/li>\n
                              • M. Wang, K. Winter, Q.-V. Dang, R. Dijkman, Detecting and Explaining Temporal Behavioral Deviations in Business Process Simulation Models<\/i><\/li>\n
                              • F. Zampino, L. Genga, A. Longo, M. S. Zappatore, R. Dijkman, A Method for Process Model Matching with LLMs<\/i><\/li>\n
                              • H. H. Beyel, M. Prokop, J. Kretinsky, G. De Giacomo, W. M. P. van der Aalst, Capturing Processes in Probabilistic Timed Automata<\/i><\/li>\n
                              • A. Gianola, Z. Hameed, M. Montali, A. Seidel, M. Weske, S. Winkler, Detecting Dynamic Relationships in Object-Centric Event Logs<\/i><\/li>\n
                              • F. Scafoglieri, M. Papandrea, T. Leidi, Towards Ontology-Guided Data Augmentation: The Case of Entity Resolution<\/i><\/li>\n
                              • A. Rozenberga, M. Kirikova, J. Stirna, Designing a Configurable Requirements Engineering Tool for Teaching<\/i><\/li>\n
                              • A. Casciani, A. Giovannetti, S. Macagnano, A. Marrella, M. L. Bernardi, M. Cimitile, F. M. Maggi, Predictive Process Monitoring via Automated Planning<\/i><\/li>\n<\/ul>\n

                                Tool papers<\/h4>\n
                                  \n
                                • S. Ahrari, A. Bernasconi, F. Invernici, A. Colombo, MLegis: Demonstrating a Property Graph-Based Information System for Legislative Analytics<\/i><\/li>\n
                                • V. Diemieniev, J. Saathoff, M. Schlegelmilch, P. Zaniewski, T.-H. Huang, G. Park, Performance Spectrum Patterns Miner<\/i><\/li>\n
                                • C. G. Moyano, F. Six, J. Mendling, PMDAgile: A Process-Model-Driven Tool for Agile Software Development<\/i><\/li>\n
                                • A. Bagozi, D. Bianchini, V. De Antonellis, M. Garda, M. Melchiori, A. Rula, D3SD: A Web-based Tool for Data Service Design in Cyber-Physical Production Networks<\/i><\/li>\n
                                • L. Bein, L. Pufahl, KARIBDIS – A Knowledge-graph-based Business Process Management System for Semantically Explainable Process Execution Support<\/i><\/li>\n
                                • A. Casciani, F. Italia, L. Lestingi, M. Marinacci, A. Marrella, A. Matta, FIDES: A Neuro-Symbolic Conversational Tool for Faithful Production Process Intelligence<\/i><\/li>\n
                                • M. Kryston, E. Marangone, A. Marcelletti, C. Di Ciccio, CONFETTY: A Tool for Enforcement and Data Confidentiality on Blockchain-Based Processes<\/i><\/li>\n<\/ul>\n

                                  Doctoral consortium<\/h2>\n

                                  Process Mining: Supporting Analysis and Use in Practice<\/h4>\n
                                    \n
                                  • Z. Ahmadi, Interactive Context-Aware Navigation of Process Models<\/i><\/li>\n
                                  • A. Claude, Scaffolding Hypothesis Testing in Process Mining through AI-Mediated Analytical Role Simulation<\/i><\/li>\n
                                  • A. Sekulovska, The impact of process mining archetypes on business process performance<\/i><\/li>\n<\/ul>\n

                                    Requirements Engineering<\/h4>\n
                                      \n
                                    • F. Hollauf, Engineering Temporal Requirements<\/i><\/li>\n
                                    • J. Kollmorgen, Beyond the User\u2013Product Relationship: Extending the Scope of UX Evaluation<\/i><\/li>\n
                                    • A. Slupczynski, A Modernization Decision Framework for Legacy Information Systems<\/i><\/li>\n<\/ul>\n

                                      Data Foundation for Information System Engineering<\/h4>\n
                                        \n
                                      • H. Hooshyar, Object-Centric Event Data: Conceptualization, Extraction and Querying<\/i><\/li>\n
                                      • V. Chan, Integrating Geospatial Data into Business Process Management<\/i><\/li>\n<\/ul>\n

                                        Tutorials<\/h2>\n
                                          \n
                                        • M. Vitali, S. Werner, Evaluating the Sustainability of Information Systems<\/i><\/li>\n
                                        • A. Casciani, L. Lestingi, A. Marrella, A. Matta, Developing Neuro-Symbolic Conversational Systems for Reliable Multi-Perspective Production Process Intelligence<\/i><\/li>\n
                                        • I. Donadello, F. M. Maggi, J. Oukharijane, Declarative Process Mining for Adaptive Information Systems: the Declare4Py Python library<\/i><\/li>\n<\/ul>\n

                                          Journal first track<\/h2>\n
                                            \n
                                          • J. Peeperkorn, J. De Smedt, J. De Weerdt, Model-driven stochastic trace clustering<\/i><\/li>\n
                                          • A. Karunaratne, A. Polyvyanyy, A. Moffat, The Effects of Log Noise in Process Mining<\/i><\/li>\n
                                          • S. Brinkkemper, S. Molenaar, F. Dalpiaz, Concept Definition Review: A Method for Studying Terminology in Software Engineering<\/i><\/li>\n
                                          • A. Bagozi, D. Bianchini, M. Garda, M. Melchiori, A. Rula, A multi-layered data service model for Cyber-Physical Production Networks<\/i><\/li>\n
                                          • A. Bagozi, D. Bianchini, M. Garda, M. Melchiori, A. Rula, Ontology-enhanced RAG for a personalised and sustainable food advisory system<\/i><\/li>\n
                                          • F. Corradini, A. Marcelletti, A. Morichetta, B. Re, L. Verducci, A Mapping Methodology Enabling Object-Centric Process Mining on Blockchain Applications<\/i><\/li>\n
                                          • F. Corradini, A. Galassi, A. Marcelletti, B. Re, CoBlock: a Domain-Specific Language for Compliance Checking on Smart Contract Execution Data<\/i><\/li>\n
                                          • R. Eshuis, A. Ghose, Synthesizing goal models from declarative data-centric process models<\/i><\/li>\n
                                          • A. Andreou, M. Bernabei, A. Christoforou, S. Colabianchi, F. Costantino, F. Leotta, J. G. Mathew, M. Mecella, F. Monti, Assessing smart manufacturing by combining IT systems and enabling technologies in a fuzzy cognitive maturity model<\/i><\/li>\n
                                          • F. Bianchini, A. M. Braccini, F. De Luzi, M. Macr\u00ec, M. Mecella, Exploring AI Chatbot Adoption for Knowledge Workers: A Unified Theory of Acceptance and Use of Technology Extension<\/i><\/li>\n
                                          • M. Barrientos, K. Winter, S. Rinderle-Ma, Impact analysis of regulatory requirement changes on business process compliance<\/i><\/li>\n
                                          • Q. Shen, A. Polyvyanyy, N. Lipovetzky, T. Kampik, Applying organizational mining to discover agent systems from event data<\/i><\/li>\n
                                          • A. Buliga, C. Di Francescomarino, C. Ghidini, I. Donadello, F. M. Maggi, Guiding the generation of counterfactual explanations through temporal background knowledge for predictive process monitoring<\/i><\/li>\n
                                          • B. Pernici, C. Cappiello, C. A. Bono, C. Sancricca, T. Catarci, M. Angelini, M. Filosa, M. Palmonari, F. De Paoli, S. Bergamaschi, G. Simonini, A. Mozzillo, L. Zecchini, Sustainable quality in data preparation<\/i><\/li>\n<\/ul>\n

                                            Research Project Exhibition Track<\/h2>\n

                                            list available soon<\/p>\n","protected":false},"excerpt":{"rendered":"

                                            Accepted Papers Main conference Enterprise Intelligence, Complexity, and Decision Support M. Schnellmann, H. A. Proper, From Gut Feeling to Data-Driven Decisions: Exploring Digital Twin supported Decision-Making for Real Estate Management J. L. R. Moreira, E. Stoica, J. P. S. Piest, F. Bukhsh, W. Levelt, A Measurement Method for Quantifying Application Landscape Complexity with Enterprise Architecture […]<\/p>\n","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-948","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/caise26.polimi.it\/index.php?rest_route=\/wp\/v2\/pages\/948","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/caise26.polimi.it\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/caise26.polimi.it\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/caise26.polimi.it\/index.php?rest_route=\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/caise26.polimi.it\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=948"}],"version-history":[{"count":30,"href":"https:\/\/caise26.polimi.it\/index.php?rest_route=\/wp\/v2\/pages\/948\/revisions"}],"predecessor-version":[{"id":995,"href":"https:\/\/caise26.polimi.it\/index.php?rest_route=\/wp\/v2\/pages\/948\/revisions\/995"}],"wp:attachment":[{"href":"https:\/\/caise26.polimi.it\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=948"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}