Ghent University Academic Bibliography

Your filters: cql: author="De Weerdt, Jochen" or (type any "bookEditor issueEditor" and editor="De Weerdt, Jochen")

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Validation set sampling strategies for predictive process monitoring

Jari Peeperkorn, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2024) INFORMATION SYSTEMS. 121.
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Hellinger distance decision trees for PU learning in imbalanced data sets

Carlos Ortega Vázquez, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2024) MACHINE LEARNING. 113(7). p.4547-4578
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GeoRF : a geospatial random forest

Margot Geerts, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2024) DATA MINING AND KNOWLEDGE DISCOVERY. 38(6). p.3414-3448
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Graph neural networks for house price prediction : do or don't?

Margot Geerts, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2024) INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS.
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LS-ICE : a load state intercase encoding framework for improved predictive monitoring of business processes

Björn Rafn Gunnarsson, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2024) INFORMATION SYSTEMS. 125.
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A two-step anomaly detection based method for PU classification in imbalanced data sets

Carlos Ortega Vázquez, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2023) DATA MINING AND KNOWLEDGE DISCOVERY. 37(3). p.1301-1325
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An evolutionary geospatial regression tree

Margot Geerts, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2023) STRL 2023 : spatio-temporal reasoning and learning 2023. In CEUR workshop proceedings 3475.
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A survey of methods and input data types for house price prediction

Margot Geerts, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2023) ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION. 12(5).
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Global conformance checking measures using shallow representation and deep learning

Jari Peeperkorn, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2023) ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE. 123(Part B).
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- Journal Article
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Can recurrent neural networks learn process model structure?

Jari Peeperkorn, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2023) JOURNAL OF INTELLIGENT INFORMATION SYSTEMS. 61(1). p.27-51
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DyLoPro : profiling the dynamics of event logs

Brecht Wuyts, Hans Weytjens, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2023) Business process management : 21st International Conference, BPM 2023, Proceedings. In Lecture notes in computer science 14159. p.146-162
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Outcome-oriented predictive process monitoring on positive and unlabelled event logs

Jari Peeperkorn, Carlos Ortega Vázquez, Alexander Stevens, Johannes De Smedt, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2023) Process Mining Workshops, ICPM 2022 International Workshops, Revised Selected Papers. In Lecture notes in business information processing 468. p.255-268
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Can deep neural networks learn process model structure? An assessment framework and analysis

Jari Peeperkorn, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2022) PROCESS MINING WORKSHOPS, ICPM 2021. In Lecture Notes in Business Information Processing 433. p.127-139
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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

Margot Geerts, Kiran Shaikh, Jochen De Weerdt and Seppe vanden Broucke (UGent)

(2022) Research Challenges in Information Science, 16th International Conference, RCIS 2022, Proceedings. In Lecture notes in business information processing 446. p.703-710
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Supervised conformance checking using recurrent neural network classifiers

Jari Peeperkorn, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2021) Process Mining Workshops, ICPM 2020 International Workshops, Revised Selected Papers. In Lecture Notes in Business Information Processing 406. p.175-187
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Expert-driven trace clustering with instance-level constraints

Pieter De Koninck, Klaas Nelissen, Seppe vanden Broucke (UGent) , Bart Baesens, Monique Snoeck and Jochen De Weerdt

(2021) KNOWLEDGE AND INFORMATION SYSTEMS. 63(5). p.1197-1220
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Conformance checking using activity and trace embeddings

Jari Peeperkorn, Seppe vanden Broucke (UGent) and Jochen De Weerdt

(2020) Business process management forum, Proceedings. In Lecture notes in business information processing 392. p.105-121
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A comparative study of representation learning techniques for dynamic networks

Carlos Ortega Vázquez, Sandra Mitrović, Jochen De Weerdt and Seppe vanden Broucke (UGent)

(2020) Trends and innovations in information systems and technologies : volume 3. In Advances in intelligent systems and computing 1161. p.523-530
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Recommendations for enhancing the usability and understandability of process mining in healthcare

Niels Martin, Jochen De Weerdt, Carlos Fernandez-Llatas, Avigdor Gal, Roberto Gatta, Gema Ibanez, Owen Johnson, Felix Mannhardt, Luis Marco-Ruiz, Steven Mertens (UGent) , et al.

(2020) ARTIFICIAL INTELLIGENCE IN MEDICINE. 109.
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Introduction to the 13th International Workshop on Business Process Intelligence (BPI 2017)

Boudewijn van Dongen, Jochen De Weerdt, Andrea Burattin and Jan Claes (UGent)

(2018) BUSINESS PROCESS MANAGEMENT WORKSHOPS (BPM 2017). In Lecture Notes in Business Information Processing 308. p.162-164
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Mixed-paradigm process modeling with intertwined state spaces

Johannes De Smedt, Jochen De Weerdt, Jan Vanthienen and Geert Poels (UGent)

(2016) BUSINESS & INFORMATION SYSTEMS ENGINEERING. 58(1). p.19-29
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A multi-dimensional quality assessment of state-of-the-art process discovery algorithms using real-life event logs

Jochen De Weerdt, Manu De Backer (UGent) , Jan Vanthienen and Bart Baesens

(2012) INFORMATION SYSTEMS. 37(7). p.654-676
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A Robust F-measure for evaluating discovered process models

Jochen De Weerdt, Manu De Backer (UGent) , Jan Vanthienen and Bart Baesens

(2011) IEEE Symposium series on computational intelligence. p.148-155
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- Conference Paper
- C3
A critical evaluation study of model-log metrics in process discovery

Jochen De Weerdt, Manu De Backer (UGent) , Jan Vanthienen and Bart Baesens

(2010) International Workshops and Education Track, Abstracts.

Academic Bibliography

Validation set sampling strategies for predictive process monitoring

Hellinger distance decision trees for PU learning in imbalanced data sets

GeoRF : a geospatial random forest

Graph neural networks for house price prediction : do or don't?

LS-ICE : a load state intercase encoding framework for improved predictive monitoring of business processes

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

An evolutionary geospatial regression tree

A survey of methods and input data types for house price prediction

Global conformance checking measures using shallow representation and deep learning

Can recurrent neural networks learn process model structure?

DyLoPro : profiling the dynamics of event logs

Outcome-oriented predictive process monitoring on positive and unlabelled event logs

Can deep neural networks learn process model structure? An assessment framework and analysis

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

Supervised conformance checking using recurrent neural network classifiers

Expert-driven trace clustering with instance-level constraints

Conformance checking using activity and trace embeddings

A comparative study of representation learning techniques for dynamic networks

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

Introduction to the 13th International Workshop on Business Process Intelligence (BPI 2017)

Mixed-paradigm process modeling with intertwined state spaces

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

A Robust F-measure for evaluating discovered process models

A critical evaluation study of model-log metrics in process discovery

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