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Johannes De Smedt
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2020 – today
- 2024
- [j26]Marco Gregnanin, Yanyi Zhang, Johannes De Smedt, Giorgio Gnecco, Maurizio Parton:
Signature-based portfolio allocation: a network approach. Appl. Netw. Sci. 9(1): 54 (2024) - [j25]Johannes De Smedt
, Jochen De Weerdt
Predictive process model monitoring using long short-term memory networks. Eng. Appl. Artif. Intell. 133: 108295 (2024) - [j24]Alexander Stevens
Explainability in process outcome prediction: Guidelines to obtain interpretable and faithful models. Eur. J. Oper. Res. 317(2): 317-329 (2024) - [j23]Manon Reusens
Evaluating text classification: A benchmark study. Expert Syst. Appl. 254: 124302 (2024) - [j22]Alexandre Goossens
Extracting process-aware decision models from object-centric process data. Inf. Sci. 682: 121263 (2024) - [j21]Simon De Vos
Data-driven internal mobility: Similarity regularization gets the job done. Knowl. Based Syst. 295: 111824 (2024) - [j20]Jinxian Zhao
A complex network analysis approach to bankruptcy prediction using company relational information-based drivers. Knowl. Based Syst. 300: 112234 (2024) - [c34]Alexandre Goossens
Object-Centric Event Logs: Characteristics, Comparative Analysis and Road Map. BPM (Forum) 2024: 37-54 - [e2]Johannes De Smedt
Process Mining Workshops - ICPM 2023 International Workshops, Rome, Italy, October 23-27, 2023, Revised Selected Papers. Lecture Notes in Business Information Processing 503, Springer 2024, ISBN 978-3-031-56106-1 [contents] - [i11]Alexandre Goossens, Johannes De Smedt, Jan Vanthienen:
Extracting Process-Aware Decision Models from Object-Centric Process Data. CoRR abs/2401.14847 (2024) - [i10]Alexander Stevens, Chun Ouyang, Johannes De Smedt, Catarina Moreira:
Generating Feasible and Plausible Counterfactual Explanations for Outcome Prediction of Business Processes. CoRR abs/2403.09232 (2024) - [i9]Alexandre Goossens, Johannes De Smedt, Jan Vanthienen:
Object-Centric Event Logs: Specifications, Comparative Analysis and Refinement. CoRR abs/2405.12709 (2024) - [i8]Lien Bosmans, Jari Peeperkorn, Alexandre Goossens, Giovanni Lugaresi, Johannes De Smedt, Jochen De Weerdt:
Dynamic and Scalable Data Preparation for Object-Centric Process Mining. CoRR abs/2410.00596 (2024) - 2023
- [j19]Johannes De Smedt, Anton Yeshchenko, Artem Polyvyanyy, Jochen De Weerdt
Process model forecasting and change exploration using time series analysis of event sequence data. Data Knowl. Eng. 145: 102145 (2023) - [j18]Alexandre Goossens
Extracting Decision Model and Notation models from text using deep learning techniques. Expert Syst. Appl. 211: 118667 (2023) - [j17]Monique Snoeck
Supporting data-aware processes with MERODE. Softw. Syst. Model. 22(6): 1779-1802 (2023) - [j16]Melina Zavali, Ewelina Lacka
Shopping Hard or Hardly Shopping: Revealing Consumer Segments Using Clickstream Data. IEEE Trans. Engineering Management 70(4): 1353-1364 (2023) - [c33]Alexandre Goossens
Aligning Object-Centric Event Logs with Data-Centric Conceptual Models. BPMDS/EMMSAD@CAiSE 2023: 44-59 - [c32]Marco Gregnanin, Johannes De Smedt, Giorgio Gnecco, Maurizio Parton:
Signature-Based Community Detection for Time Series. COMPLEX NETWORKS (2) 2023: 146-158 - [c31]Alexandre Goossens
Comparing the Performance of GPT-3 with BERT for Decision Requirements Modeling. CoopIS 2023: 448-458 - [c30]Alexander Stevens, Jari Peeperkorn
Manifold Learning for Adversarial Robustness in Predictive Process Monitoring. ICPM 2023: 17-24 - [c29]Alexandre Goossens
From OCEL to DOCEL - Datasets and Automated Transformation. ICPM Workshops 2023: 70-83 - [i7]Alexandre Goossens, Adrian Rebmann, Johannes De Smedt, Jan Vanthienen, Han van der Aa:
From OCEL to DOCEL - Datasets and Automated Transformation. CoRR abs/2309.14092 (2023) - [i6]Marco Gregnanin, Johannes De Smedt, Giorgio Gnecco, Maurizio Parton:
Signature-Based Community Detection for Time Series. CoRR abs/2311.05986 (2023) - 2022
- [j15]Christopher Loynes
The detection and location estimation of disasters using Twitter and the identification of Non-Governmental Organisations using crowdsourcing. Ann. Oper. Res. 308(1): 339-371 (2022) - [j14]Galina Deeva
Predicting student performance using sequence classification with time-based windows. Expert Syst. Appl. 209: 118182 (2022) - [j13]Galina Deeva
Educational Sequence Mining for Dropout Prediction in MOOCs: Model Building, Evaluation, and Benchmarking. IEEE Trans. Learn. Technol. 15(6): 720-735 (2022) - [j12]Faruk Hasic
Decision as a Service (DaaS): A Service-Oriented Architecture Approach for Decisions in Processes. IEEE Trans. Serv. Comput. 15(2): 904-917 (2022) - [c28]Alexandre Goossens
Enhancing Data-Awareness of Object-Centric Event Logs. ICPM Workshops 2022: 18-30 - [c27]Alexander Stevens, Johannes De Smedt, Jari Peeperkorn
Assessing the Robustness in Predictive Process Monitoring through Adversarial Attacks. ICPM 2022: 56-63 - [c26]Jari Peeperkorn
Outcome-Oriented Predictive Process Monitoring on Positive and Unlabelled Event Logs. ICPM Workshops 2022: 255-268 - [i5]Galina Deeva, Johannes De Smedt, Cecilia Saint-Pierre, Richard Weber, Jochen De Weerdt:
Predicting student performance using sequence classification with time-based windows. CoRR abs/2208.07749 (2022) - [i4]Alexandre Goossens, Johannes De Smedt, Jan Vanthienen, Wil M. P. van der Aalst:
Enhancing Data-Awareness of Object-Centric Event Logs. CoRR abs/2212.02858 (2022) - 2021
- [j11]Johannes De Smedt, Ewelina Lacka, Spyro Nita, Hans-Helmut Kohls, Ross Paton:
Session stitching using sequence fingerprinting for web page visits. Decis. Support Syst. 150: 113579 (2021) - [j10]Boudewijn F. van Dongen, Johannes De Smedt
Conformance checking of mixed-paradigm process models. Inf. Syst. 102: 101685 (2021) - [c25]Monique Snoeck
Supporting Data-Aware Processes with MERODE. BPMDS/EMMSAD@CAiSE 2021: 131-146 - [c24]Johannes De Smedt
Process Model Forecasting Using Time Series Analysis of Event Sequence Data. ER 2021: 47-61 - [c23]Alexander Stevens
Quantifying Explainability in Outcome-Oriented Predictive Process Monitoring. ICPM Workshops 2021: 194-206 - [i3]Johannes De Smedt, Anton Yeshchenko, Artem Polyvyanyy, Jochen De Weerdt, Jan Mendling:
Process Model Forecasting Using Time Series Analysis of Event Sequence Data. CoRR abs/2105.01092 (2021) - 2020
- [j9]Johannes De Smedt
Mining Behavioral Sequence Constraints for Classification. IEEE Trans. Knowl. Data Eng. 32(6): 1130-1142 (2020) - [i2]Johannes De Smedt, Jochen De Weerdt, Junichiro Mori, Masanao Ochi:
Predictive Process Model Monitoring using Recurrent Neural Networks. CoRR abs/2011.02819 (2020) - [i1]Boudewijn F. van Dongen, Johannes De Smedt, Claudio Di Ciccio, Jan Mendling:
Conformance Checking of Mixed-paradigm Process Models. CoRR abs/2011.11551 (2020)
2010 – 2019
- 2019
- [j8]Anthony Simonofski, Estefanía Serral Asensio
Hearing the Voice of Citizens in Smart City Design: The CitiVoice Framework. Bus. Inf. Syst. Eng. 61(6): 665-678 (2019) - [j7]Johannes De Smedt
Holistic discovery of decision models from process execution data. Knowl. Based Syst. 183 (2019) - [c22]Galina Deeva, Johannes De Smedt
Mining Behavioural Patterns in Urban Mobility Sequences Using Foursquare Check-in Data from Tokyo. COMPLEX NETWORKS (2) 2019: 931-943 - [c21]Johannes De Smedt
Using Sequence Constraints for Modelling Network Interactions. JSAI 2019: 3-13 - [e1]Benoît Depaire, Johannes De Smedt, Marlon Dumas, Dirk Fahland, Akhil Kumar, Henrik Leopold, Manfred Reichert, Stefanie Rinderle-Ma, Stefan Schulte, Stefan Seidel, Wil M. P. van der Aalst:
Proceedings of the Dissertation Award, Doctoral Consortium, and Demonstration Track at BPM 2019 co-located with 17th International Conference on Business Process Management, BPM 2019, Vienna, Austria, September 1-6, 2019. CEUR Workshop Proceedings 2420, CEUR-WS.org 2019 [contents] - 2018
- [j6]Faruk Hasic
Augmenting processes with decision intelligence: Principles for integrated modelling. Decis. Support Syst. 107: 1-12 (2018) - [j5]Johannes De Smedt
Discovering hidden dependencies in constraint-based declarative process models for improving understandability. Inf. Syst. 74(Part): 40-52 (2018) - [c20]Faruk Hasic
Redesigning Processes for Decision-Awareness: Strategies for Integrated Modelling. QUATIC 2018: 247-250 - 2017
- [c19]Johannes De Smedt, Faruk Hasic, Seppe K. L. M. vanden Broucke, Jan Vanthienen
Towards a Holistic Discovery of Decisions in Process-Aware Information Systems. BPM 2017: 183-199 - [c18]Galina Deeva, Johannes De Smedt
Dropout Prediction in MOOCs: A Comparison Between Process and Sequence Mining. Business Process Management Workshops 2017: 243-255 - [c17]Faruk Hasic
Challenges in Refactoring Processes to Include Decision Modelling. Business Process Management Workshops 2017: 529-541 - [c16]Johannes De Smedt:
Studies on Declarative Process Modeling and Its Relation to Procedural Techniques. BPM (Demos) 2017 - [c15]Faruk Hasic, Johannes De Smedt, Jan Vanthienen:
Towards Assessing the Theoretical Complexity of the Decision Model and Notation (DMN). RADAR+EMISA@CAiSE 2017: 64-71 - [c14]Estefanía Serral
Support for Verifying Pervasive Behavior by Mapping Task Models to Petri Nets. SEAA 2017: 181-188 - [c13]Faruk Hasic
Developing a Modelling and Mining Framework for Integrated Processes and Decisions. OTM Workshops 2017: 259-269 - [c12]Faruk Hasic
A Service-Oriented Architecture Design of Decision-Aware Information Systems: Decision as a Service - (Short Paper). OTM Conferences (1) 2017: 353-361 - [c11]Johannes De Smedt
Behavioral Constraint Template-Based Sequence Classification. ECML/PKDD (2) 2017: 20-36 - [c10]Anthony Simonofski, Estefanía Serral Asensio
Citizen Participation in Smart Cities: Evaluation Framework Proposal. CBI (1) 2017: 227-236 - 2016
- [b1]Johannes De Smedt:
Studies on declarative process modeling and its relation to procedural techniques. Katholieke Universiteit Leuven, Belgium, 2016 - [j4]Johannes De Smedt
Mixed-Paradigm Process Modeling with Intertwined State Spaces. Bus. Inf. Syst. Eng. 58(1): 19-29 (2016) - [j3]Johannes De Smedt, Jochen De Weerdt
Erratum to: Mixed-Paradigm Process Modeling with Intertwined State Spaces. Bus. Inf. Syst. Eng. 58(1): 101-104 (2016) - [c9]Johannes De Smedt
Model Checking of Mixed-Paradigm Process Models in a Discovery Context - Finding the Fit Between Declarative and Procedural. Business Process Management Workshops 2016: 74-86 - [c8]Johannes De Smedt
Decision Mining in a Broader Context: An Overview of the Current Landscape and Future Directions. Business Process Management Workshops 2016: 197-207 - [c7]Johannes De Smedt, Jochen De Weerdt
Improving Understandability of Declarative Process Models by Revealing Hidden Dependencies. CAiSE 2016: 83-98 - [c6]Laurent Janssens, Ekaterina Bazhenova, Johannes De Smedt, Jan Vanthienen, Marc Denecker:
Consistent Integration of Decision (DMN) and Process (BPMN) Models. CAiSE Forum 2016: 121-128 - [c5]Laurent Janssens, Johannes De Smedt
Modeling and Enacting Enterprise Decisions. CAiSE Workshops 2016: 169-180 - 2015
- [j2]Johannes De Smedt
Fusion Miner: Process discovery for mixed-paradigm models. Decis. Support Syst. 77: 123-136 (2015) - [j1]Estefanía Serral
Context-adaptive Petri nets: Supporting adaptation for the execution context. Expert Syst. Appl. 42(23): 9307-9317 (2015) - [c4]Johannes De Smedt
Gamification of Declarative Process Models for Learning and Model Verification. Business Process Management Workshops 2015: 432-443 - 2014
- [c3]Estefanía Serral
Extending CPN Tools with Ontologies to Support the Management of Context-Adaptive Business Processes. Business Process Management Workshops 2014: 198-209 - [c2]Johannes De Smedt
Multi-paradigm Process Mining: Retrieving Better Models by Combining Rules and Sequences - (Short Paper). OTM Conferences 2014: 446-453 - [c1]Estefanía Serral
Making Business Environments Smarter: A Context-Adaptive Petri Net Approach. UIC/ATC/ScalCom 2014: 343-348
Coauthor Index
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last updated on 2024-12-10 20:51 CET by the dblp team
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