Jochen De Weerdt

Proceedings of the 5th International Conference on Process Mining, 2023

Vector Representation for Business Process: Graph Embedding for Domain Knowledge Integration.

[BibT_eX]

[DOI]

Thais Rodrigues Neubauer

Sarajane Marques Peres

Marcelo Fantinato

Proceedings of the International Conference on Machine Learning and Applications, 2023

Discovering high-quality process models despite data scarcity.

[BibT_eX]

[DOI]

Proceedings of the Companion Proceedings of the 42nd International Conference on Conceptual Modeling: ER Forum, 2023

Investigating Bias in Multilingual Language Models: Cross-Lingual Transfer of Debiasing Techniques.

[BibT_eX]

[DOI]

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

CORE: A Few-Shot Company Relation Classification Dataset for Robust Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

DyLoPro: Profiling the Dynamics of Event Logs.

[BibT_eX]

[DOI]

Proceedings of the Business Process Management - 21st International Conference, 2023

Timed Process Interventions: Causal Inference vs. Reinforcement Learning.

[BibT_eX]

[DOI]

Wouter Verbeke

Proceedings of the Business Process Management Workshops, 2023

A Novel Multi-perspective Trace Clustering Technique for IoT-Enhanced Processes: A Case Study in Smart Manufacturing.

[BibT_eX]

[DOI]

Yannis Bertrand

Estefanía Serral

Proceedings of the Business Process Management - 21st International Conference, 2023

2022

Educational Sequence Mining for Dropout Prediction in MOOCs: Model Building, Evaluation, and Benchmarking.

[BibT_eX]

[DOI]

IEEE Trans. Learn. Technol., 2022

Predicting student performance using sequence classification with time-based windows.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2022

Inductive Graph Representation Learning for fraud detection.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2022

Learning Uncertainty with Artificial Neural Networks for Improved Predictive Process Monitoring.

[BibT_eX]

[DOI]

CoRR, 2022

Learning uncertainty with artificial neural networks for predictive process monitoring.

[BibT_eX]

[DOI]

Appl. Soft Comput., 2022

Predicting the State of a House Using Google Street View - An Analysis of Deep Binary Classification Models for the Assessment of the Quality of Flemish Houses.

[BibT_eX]

[DOI]

Proceedings of the Research Challenges in Information Science, 2022

The Hidden Cost of Fraud: An Instance-Dependent Cost-Sensitive Approach for Positive and Unlabeled Learning.

[BibT_eX]

[DOI]

Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2022

A framework for encoding the multi-location load state of a business process.

[BibT_eX]

[DOI]

Björn Rafn Gunnarsson

Proceedings of the Workshop on Process Management in the AI Era (PMAI 2022) co-located with 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI 2022), 2022

Assessing the Robustness in Predictive Process Monitoring through Adversarial Attacks.

[BibT_eX]

[DOI]

Proceedings of the 4th International Conference on Process Mining, 2022

Outcome-Oriented Predictive Process Monitoring on Positive and Unlabelled Event Logs.

[BibT_eX]

[DOI]

Proceedings of the Process Mining Workshops, 2022

Defining Data Quality Issues in Process Mining with IoT Data.

[BibT_eX]

[DOI]

Proceedings of the Process Mining Workshops, 2022

Assessing the Suitability of Traditional Event Log Standards for IoT-Enhanced Event Logs.

[BibT_eX]

[DOI]

Yannis Bertrand

Estefanía Serral

Proceedings of the Business Process Management Workshops, 2022

Evaluation of Joint Modeling Techniques for Node Embedding and Community Detection on Graphs.

[BibT_eX]

[DOI]

Simon Hiel

Lore Nicolaers

Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2022

Enhancing Stochastic Petri Net-based Remaining Time Prediction using k-Nearest Neighbors.

[BibT_eX]

[DOI]

Proceedings of the Workshop on Algorithms & Theories for the Analysis of Event Data co-located with the 43rd International Conference on Application and Theory of Petri Nets and Concurrency (Petri Nets 2022), 2022

Foundations of Process Event Data.

[BibT_eX]

[DOI]

Proceedings of the Process Mining Handbook, 2022

2021

Expert-driven trace clustering with instance-level constraints.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2021

tcc2vec: RFM-informed representation learning on call graphs for churn prediction.

[BibT_eX]

[DOI]

Inf. Sci., 2021

Conformance Checking in Process Mining.

[BibT_eX]

[DOI]

Inf. Syst., 2021

Special issue on business process intelligence.

[BibT_eX]

[DOI]

Andrea Burattin

Boudewijn F. van Dongen

Jan Claes

Computing, 2021

A review of automated feedback systems for learners: Classification framework, challenges and opportunities.

[BibT_eX]

[DOI]

Comput. Educ., 2021

Can Deep Neural Networks Learn Process Model Structure? An Assessment Framework and Analysis.

[BibT_eX]

[DOI]

Proceedings of the Process Mining Workshops - ICPM 2021 International Workshops, Eindhoven, The Netherlands, October 31, 2021

A Bridging Model for Process Mining and IoT.

[BibT_eX]

[DOI]

Yannis Bertrand

Estefanía Serral

Proceedings of the Process Mining Workshops - ICPM 2021 International Workshops, Eindhoven, The Netherlands, October 31, 2021

Neural Machine Translation for Conditional Generation of Novel Procedures.

[BibT_eX]

[DOI]

Joppe Geluykens

Teodoro Laino

Alain C. Vaucher

Proceedings of the 54th Hawaii International Conference on System Sciences, 2021

Process Model Forecasting Using Time Series Analysis of Event Sequence Data.

[BibT_eX]

[DOI]

Proceedings of the Conceptual Modeling - 40th International Conference, 2021

Supporting Data-Aware Processes with MERODE.

[BibT_eX]

[DOI]

Proceedings of the Enterprise, Business-Process and Information Systems Modeling, 2021

Creating Unbiased Public Benchmark Datasets with Data Leakage Prevention for Predictive Process Monitoring.

[BibT_eX]

[DOI]

Proceedings of the Business Process Management Workshops, 2021

Learning Uncertainty with Artificial Neural Networks for Improved Remaining Time Prediction of Business Processes.

[BibT_eX]

[DOI]

Proceedings of the Business Process Management - 19th International Conference, 2021

2020

Mining Behavioral Sequence Constraints for Classification.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2020

Churn modeling with probabilistic meta paths-based representation learning.

[BibT_eX]

[DOI]

Inf. Process. Manag., 2020

Predictive Process Model Monitoring using Recurrent Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2020

Recommendations for enhancing the usability and understandability of process mining in healthcare.

[BibT_eX]

[DOI]

Niels Martin

Carlos Fernández-Llatas

Artif. Intell. Medicine, 2020

A Comparative Study of Representation Learning Techniques for Dynamic Networks.

[BibT_eX]

[DOI]

Proceedings of the Trends and Innovations in Information Systems and Technologies, 2020

Predicting student success in a blended learning environment.

[BibT_eX]

[DOI]

Steven Van Goidsenhoven

Proceedings of the LAK '20: 10th International Conference on Learning Analytics and Knowledge, 2020

Supervised Conformance Checking Using Recurrent Neural Network Classifiers.

[BibT_eX]

[DOI]

Proceedings of the Process Mining Workshops, 2020

Process Outcome Prediction: CNN vs. LSTM (with Attention).

[BibT_eX]

[DOI]

Proceedings of the Business Process Management Workshops, 2020

Conformance Checking Using Activity and Trace Embeddings.

[BibT_eX]

[DOI]

Proceedings of the Business Process Management Forum, 2020

2019

Trace Clustering.

[BibT_eX]

[DOI]

Proceedings of the Encyclopedia of Big Data Technologies., 2019

A Comparative Study of Community Detection Techniques for Large Evolving Graphs.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Representation Learning in Graphs for Credit Card Fraud Detection.

[BibT_eX]

[DOI]

Rafaël Van Belle

Proceedings of the Mining Data for Financial Applications - 4th ECML PKDD Workshop, 2019

Scalable Mixed-Paradigm Trace Clustering using Super-Instances.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Process Mining, 2019

Optimizing Marketing Campaign Targeting Using Uncertainty-Based Predictive Modelling.

[BibT_eX]

[DOI]

Björn Rafn Gunnarsson

Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

Mining Behavioural Patterns in Urban Mobility Sequences Using Foursquare Check-in Data from Tokyo.

[BibT_eX]

[DOI]

Proceedings of the Complex Networks and Their Applications VIII, 2019

Predictive Process Monitoring in Operational Logistics: A Case Study in Aviation.

[BibT_eX]

[DOI]

Björn Rafn Gunnarsson

Proceedings of the Business Process Management Workshops, 2019

A comparison of methods for link sign prediction with signed network embeddings.

[BibT_eX]

[DOI]

Laurent Lecoutere

Proceedings of the ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining, 2019

2018

Discovering hidden dependencies in constraint-based declarative process models for improving understandability.

[BibT_eX]

[DOI]

Inf. Syst., 2018

On the operational efficiency of different feature types for telco Churn prediction.

[BibT_eX]

[DOI]

Eur. J. Oper. Res., 2018

Discovering the Impact of Students' Modeling Behavior on their Final Performance.

[BibT_eX]

[DOI]

Proceedings of the Practice of Enterprise Modeling - 11th IFIP WG 8.1. Working Conference, PoEM 2018, Vienna, Austria, October 31, 2018

act2vec, trace2vec, log2vec, and model2vec: Representation Learning for Business Processes.

[BibT_eX]

[DOI]

Proceedings of the Business Process Management - 16th International Conference, 2018

Understanding Automated Feedback in Learning Processes by Mining Local Patterns.

[BibT_eX]

[DOI]

Proceedings of the Business Process Management Workshops, 2018

Combining Temporal Aspects of Dynamic Networks with Node2Vec for a more Efficient Dynamic Link Prediction.

[BibT_eX]

[DOI]

Proceedings of the IEEE/ACM 2018 International Conference on Advances in Social Networks Analysis and Mining, 2018

2017

Similarity-Based Approaches for Determining the Number of Trace Clusters in Process Discovery.

[BibT_eX]

[DOI]

Trans. Petri Nets Other Model. Concurr., 2017

Change visualisation: Analysing the resource and timing differences between two event logs.

[BibT_eX]

[DOI]

Wei Zhe Low

Inf. Syst., 2017

Fodina: A robust and flexible heuristic process discovery technique.

[BibT_eX]

[DOI]

Decis. Support Syst., 2017

Explaining clusterings of process instances.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2017

Behavioral Constraint Template-Based Sequence Classification.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Churn Prediction Using Dynamic RFM-Augmented Node2vec.

[BibT_eX]

[DOI]

Proceedings of the Personal Analytics and Privacy. An Individual and Collective Perspective, 2017

Scalable RFM-enriched Representation Learning for Churn Prediction.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

An Approach for Incorporating Expert Knowledge in Trace Clustering.

[BibT_eX]

[DOI]

Proceedings of the Advanced Information Systems Engineering, 2017

Dropout Prediction in MOOCs: A Comparison Between Process and Sequence Mining.

[BibT_eX]

[DOI]

Proceedings of the Business Process Management Workshops, 2017

2016

Revising history for cost-informed process improvement.

[BibT_eX]

[DOI]

Wei Zhe Low

Computing, 2016

Process-mining enabled feedback: "Tell me what I did wrong" vs. "tell me how to do it right".

[BibT_eX]

[DOI]

Gayane Sedrakyan

Comput. Hum. Behav., 2016

Erratum to: Mixed-Paradigm Process Modeling with Intertwined State Spaces.

[BibT_eX]

[DOI]

Bus. Inf. Syst. Eng., 2016

Mixed-Paradigm Process Modeling with Intertwined State Spaces.

[BibT_eX]

[DOI]

Bus. Inf. Syst. Eng., 2016

Automating immediate and personalized feedback taking conceptual modelling education to a next level.

[BibT_eX]

[DOI]

Proceedings of the Tenth IEEE International Conference on Research Challenges in Information Science, 2016

Improving Understandability of Declarative Process Models by Revealing Hidden Dependencies.

[BibT_eX]

[DOI]

Proceedings of the Advanced Information Systems Engineering, 2016

Multi-objective Trace Clustering: Finding More Balanced Solutions.

[BibT_eX]

[DOI]

Proceedings of the Business Process Management Workshops, 2016

A Stability Assessment Framework for Process Discovery Techniques.

[BibT_eX]

[DOI]

Proceedings of the Business Process Management - 14th International Conference, 2016

Determining the Number of Trace Clusters: a Stability-based Approach.

[BibT_eX]

[DOI]

Proceedings of the International Workshop on Algorithms & Theories for the Analysis of Event Data 2016 Satellite event of the conferences: 37th International Conference on Application and Theory of Petri Nets and Concurrency Petri Nets 2016 and 16th International Conference on Application of Concurrency to System Design ACSD 2016, 2016

2015

Fusion Miner: Process discovery for mixed-paradigm models.

[BibT_eX]

[DOI]

Decis. Support Syst., 2015

Gamification of Declarative Process Models for Learning and Model Verification.

[BibT_eX]

[DOI]

Proceedings of the Business Process Management Workshops - BPM 2015, 13th International Workshops, Innsbruck, Austria, August 31, 2015

2014

Determining Process Model Precision and Generalization with Weighted Artificial Negative Events.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2014

Controlled automated discovery of collections of business process models.

[BibT_eX]

[DOI]

Luciano García-Bañuelos

Marlon Dumas

Marcello La Rosa

Chathura C. Ekanayake

Inf. Syst., 2014

Process mining analysis of conceptual modeling behavior of novices - empirical study using JMermaid modeling and experimental logging environment.

[BibT_eX]

[DOI]

Gayane Sedrakyan

Comput. Hum. Behav., 2014

Monitoring care processes in the gynecologic oncology department.

[BibT_eX]

[DOI]

Comput. Biol. Medicine, 2014

Multi-paradigm Process Mining: Retrieving Better Models by Combining Rules and Sequences - (Short Paper).

[BibT_eX]

[DOI]

Proceedings of the On the Move to Meaningful Internet Systems: OTM 2014 Conferences, 2014

Perturbing event logs to identify cost reduction opportunities: A genetic algorithm-based approach.

[BibT_eX]

[DOI]

Wei Zhe Low

Proceedings of the IEEE Congress on Evolutionary Computation, 2014

Bidimensional Process Discovery for Mining BPMN Models.

[BibT_eX]

[DOI]

Filip Caron

Proceedings of the Business Process Management Workshops, 2014

SECPI: Searching for Explanations for Clustered Process Instances.

[BibT_eX]

[DOI]

Proceedings of the Business Process Management - 12th International Conference, 2014

2013

Active Trace Clustering for Improved Process Discovery.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2013

Process Mining for the multi-faceted analysis of business processes - A case study in a financial services organization.

[BibT_eX]

[DOI]

Comput. Ind., 2013

A comprehensive benchmarking framework (CoBeFra) for conformance analysis between procedural process models and event logs in ProM.

[BibT_eX]

[DOI]

Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2013

Report: Business Process Intelligence Challenge 2013.

[BibT_eX]

[DOI]

Boudewijn F. van Dongen

Barbara Weber

Diogo R. Ferreira

Proceedings of the Business Process Management Workshops, 2013

Cost-Aware Business Process Management: A Research Agenda.

[BibT_eX]

[DOI]

Moe Wynn

Proceedings of the Australasian Conference on Information Systems, 2013

2012

Business process discovery: new techniques and applications.

[BibT_eX]

[DOI]

PhD thesis, 2012

A multi-dimensional quality assessment of state-of-the-art process discovery algorithms using real-life event logs.

[BibT_eX]

[DOI]

Inf. Syst., 2012

Getting a Grasp on Clinical Pathway Data: An Approach Based on Process Mining.

[BibT_eX]

[DOI]

Proceedings of the Emerging Trends in Knowledge Discovery and Data Mining - PAKDD 2012 International Workshops: DMHM, GeoDoc, 3Clust, and DSDM, Kuala Lumpur, Malaysia, May 29, 2012

Leveraging process discovery with trace clustering and text mining for intelligent analysis of incident management processes.

[BibT_eX]

[DOI]

Proceedings of the IEEE Congress on Evolutionary Computation, 2012

Improved Artificial Negative Event Generation to Enhance Process Event Logs.

[BibT_eX]

[DOI]