Ghent University Academic Bibliography

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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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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

Academic Bibliography

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

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)

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