Seppe vanden Broucke

Seppe vanden Broucke

Katholieke Universiteit Leuven

H-index: 26

Europe-Belgium

About Seppe vanden Broucke

Seppe vanden Broucke, With an exceptional h-index of 26 and a recent h-index of 21 (since 2020), a distinguished researcher at Katholieke Universiteit Leuven, specializes in the field of Process and Data Science, Management Informatics, Analytics, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Validation set sampling strategies for predictive process monitoring

A two-step anomaly detection based method for PU classification in imbalanced data sets

Can recurrent neural networks learn process model structure?

Explainable Deep Learning to Classify Royal Navy Ships

Hellinger distance decision trees for PU learning in imbalanced data sets

Global conformance checking measures using shallow representation and deep learning

A bagging-based selective ensemble model for churn prediction on imbalanced data

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

Seppe vanden Broucke Information

University

Position

Assistant Professor at UGent Lecturer at

Citations(all)

2081

Citations(since 2020)

1598

Cited By

945

hIndex(all)

26

hIndex(since 2020)

21

i10Index(all)

47

i10Index(since 2020)

37

Email

University Profile Page

Katholieke Universiteit Leuven

Google Scholar

View Google Scholar Profile

Seppe vanden Broucke Skills & Research Interests

Process and Data Science

Management Informatics

Analytics

Machine Learning

Top articles of Seppe vanden Broucke

Title

Journal

Author(s)

Publication Date

Validation set sampling strategies for predictive process monitoring

Information Systems

Jari Peeperkorn

Seppe vanden Broucke

Jochen De Weerdt

2024/3/1

A two-step anomaly detection based method for PU classification in imbalanced data sets

Data Mining and Knowledge Discovery

Carlos Ortega Vázquez

Seppe vanden Broucke

Jochen De Weerdt

2023/5

Can recurrent neural networks learn process model structure?

Journal of Intelligent Information Systems

Jari Peeperkorn

Seppe vanden Broucke

Jochen De Weerdt

2022/12/1

Explainable Deep Learning to Classify Royal Navy Ships

Ieee Access

Bart Baesens

Amy Adams

Rodrigo Pacheco-Ruiz

Ann-Sophie Baesens

Seppe Vanden Broucke

2023/12/22

Hellinger distance decision trees for PU learning in imbalanced data sets

Machine Learning

Carlos Ortega Vázquez

Seppe vanden Broucke

Jochen De Weerdt

2023/3/28

Global conformance checking measures using shallow representation and deep learning

Engineering Applications of Artificial Intelligence

Jari Peeperkorn

Seppe vanden Broucke

Jochen De Weerdt

2023/8/1

A bagging-based selective ensemble model for churn prediction on imbalanced data

Expert systems with applications

Bing Zhu

Cheng Qian

Seppe vanden Broucke

Jin Xiao

2023/4/20

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

Jari Peeperkorn

Carlos Ortega Vázquez

Alexander Stevens

Johannes De Smedt

Seppe vanden Broucke

...

2022/10/23

Regularization oversampling for classification tasks: To exploit what you do not know

Information Sciences

Lennert Van der Schraelen

Kristof Stouthuysen

Seppe Vanden Broucke

Tim Verdonck

2023/7/1

Toward Data Protection by Design: Assessing the Current State of GDPR Disclosure in Web Applications

Abdel-Jaouad Aberkane

Seppe vanden Broucke

Geert Poels

2023/9/4

A direct data aware LSTM neural network architecture for complete remaining trace and runtime prediction

IEEE Transactions on Services Computing

Björn Rafn Gunnarsson

Seppe vanden Broucke

Jochen De Weerdt

2023/2/16

A review and experimental evaluation of the state-of-the-art in text classification

Manon Reusens

Alexander Stevens

Jonathan Tonglet

Johannes De Smedt

Wouter Verbeke

...

2023/5/25

An Evolutionary Geospatial Regression Tree

Proceedings of the 2nd International Workshop on Spatio-Temporal Reasoning and Learning (STRL 2023) co-located with the 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023)

Margot Geerts

Jochen De Weerdt

2023/9/4

Geospatial Prediction Using Road Topology: A Graph-based Perspective

Yameng Guo

Seppe vanden Broucke

2023

A Survey of Methods and Input Data Types for House Price Prediction

Margot Geerts

Jochen De Weerdt

2023/5

DyLoPro: Profiling the Dynamics of Event Logs

Brecht Wuyts

Hans Weytjens

Seppe vanden Broucke

Jochen De Weerdt

2023/9/1

Benchmark Study for Flemish Twitter Sentiment Analysis

Available at SSRN 4096559

Manon Reusens

Michael Reusens

Marc Callens

Seppe Vanden Broucke

Bart Baesens

2022

Investigating Organizational Factors Associated with GDPR Noncompliance using Privacy Policies: A Machine Learning Approach

Abdel-Jaouad Aberkane

Seppe Vanden Broucke

Geert Poels

2022/12/14

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

Björn Rafn Gunnarsson

Jochen De Weerdt

Seppe vanden Broucke

2022

Comparison of Different Modeling Techniques for Flemish Twitter Sentiment Analysis

Analytics

Manon Reusens

Michael Reusens

Marc Callens

Seppe vanden Broucke

Bart Baesens

2022/10/18

See List of Professors in Seppe vanden Broucke University(Katholieke Universiteit Leuven)

Co-Authors

H-index: 76
Bart Baesens

Bart Baesens

Katholieke Universiteit Leuven

H-index: 56
Jan Vanthienen

Jan Vanthienen

Katholieke Universiteit Leuven

H-index: 38
Josep Carmona

Josep Carmona

Universidad Politécnica de Cataluña

H-index: 31
Jochen De Weerdt

Jochen De Weerdt

Katholieke Universiteit Leuven

H-index: 20
Johannes De Smedt

Johannes De Smedt

Katholieke Universiteit Leuven

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