Ghent University Academic Bibliography

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Exploring the performance of continuous-time dynamic link prediction algorithms

Raphaël Romero (UGent) , Maarten Buyl (UGent) , Tijl De Bie (UGent) and Jefrey Lijffijt (UGent)

(2024) APPLIED SCIENCES-BASEL. 14(8).
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Scalable job recommendation with lower congestion using optimal transport

Yoosof Mashayekhi (UGent) , Bo Kang (UGent) , Jefrey Lijffijt (UGent) and Tijl De Bie (UGent)

(2024) IEEE ACCESS. 12. p.55491-55505
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FEIR : quantifying and reducing envy and inferiority for fair recommendation of limited resources

Nan Li (UGent) , Bo Kang (UGent) , Jefrey Lijffijt (UGent) and Tijl De Bie (UGent)

(2024) ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY. 15(4). p.1-24
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GREASE : graph imbalance reduction by adding sets of edges

Yoosof Mashayekhi (UGent) , Bo Kang (UGent) , Jefrey Lijffijt (UGent) and Tijl De Bie (UGent)

(2024) IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING. 36(4). p.1611-1623
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Pattern or artifact? Interactively exploring embedding quality with TRACE

Edith Heiter (UGent) , Liesbet Martens (UGent) , Ruth Seurinck (UGent) , Martin Guilliams (UGent) , Tijl De Bie (UGent) , Yvan Saeys (UGent) and Jefrey Lijffijt (UGent)

(2024) MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES-RESEARCH TRACK AND DEMO TRACK, PT VIII, ECML PKDD 2024. In Lecture Notes in Computer Science 14948. p.379-382
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Incorporating topological priors into low-dimensional visualizations through topological regularization

Edith Heiter (UGent) , Robin Vandaele, Tijl De Bie (UGent) , Yvan Saeys (UGent) and Jefrey Lijffijt (UGent)

(2024) IEEE ACCESS. 12. p.129541-129573
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A challenge-based survey of e-recruitment recommendation systems

Yoosof Mashayekhi (UGent) , Nan Li (UGent) , Bo Kang (UGent) , Jefrey Lijffijt (UGent) and Tijl De Bie (UGent)

(2024) ACM COMPUTING SURVEYS. 56(10).
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Large language models reflect the ideology of their creators

Maarten Buyl (UGent) , Alexander Rogiers (UGent) , Sander Noels (UGent) , Iris Dominguez-Catena, Edith Heiter (UGent) , Raphaël Romero (UGent) , Iman Johary (UGent) , Alexandru-Cristian Mara (UGent) , Jefrey Lijffijt (UGent) and Tijl De Bie (UGent)

(2024) ARXIV.
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An empirical evaluation of network representation learning methods

Alexandru-Cristian Mara (UGent) , Jefrey Lijffijt (UGent) and Tijl De Bie (UGent)

(2024) BIG DATA. 12(6). p.518-537
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Gaussian embedding of temporal networks

Raphaël Romero (UGent) , Jefrey Lijffijt (UGent) , Riccardo Rastelli, Marco Corneli and Tijl De Bie (UGent)

(2023) IEEE ACCESS. 11. p.117971-117983
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FEIR : quantifying and reducing envy and inferiority for fair recommendation of limited resources

Nan Li (UGent) , Bo Kang (UGent) , Jefrey Lijffijt (UGent) and Tijl De Bie (UGent)

(2023) RECSYS in HR 2023 : the 3rd Workshop on Recommender Systems for Human Resources (RecSys in HR 2023), Proceedings. In CEUR workshop proceedings 3490.
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Revised conditional t-SNE : looking beyond the nearest neighbors

Edith Heiter (UGent) , Bo Kang (UGent) , Ruth Seurinck (UGent) and Jefrey Lijffijt (UGent)

(2023) Advances in Intelligent Data Analysis XXI : 21st International Symposium on Intelligent Data Analysis, IDA 2023, Proceedings. In Lecture notes in computer science 13876. p.169-181
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ReCon : reducing congestion in job recommendation using optimal transport

Yoosof Mashayekhi (UGent) , Bo Kang (UGent) , Jefrey Lijffijt (UGent) and Tijl De Bie (UGent)

(2023) Proceedings of the 17th ACM Conference on Recommender Systems (RecSys 2023). p.696-701
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- Miscellaneous
Topologically regularized data embeddings

Edith Heiter (UGent) , Robin Vandaele, Tijl De Bie (UGent) , Yvan Saeys (UGent) and Jefrey Lijffijt (UGent)

(2023)
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EvalNE : a framework for network embedding evaluation

Alexandru-Cristian Mara (UGent) , Jefrey Lijffijt (UGent) and Tijl De Bie (UGent)

(2022) SOFTWAREX. 17.
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A challenge-based survey of e-recruitment recommendation systems

Yoosof Mashayekhi (UGent) , Nan Li (UGent) , Bo Kang (UGent) , Jefrey Lijffijt (UGent) and Tijl De Bie (UGent)

(2022)
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A systematic evaluation of node embedding robustness

Alexandru-Cristian Mara (UGent) , Jefrey Lijffijt (UGent) , Stephan Günnemann and Tijl De Bie (UGent)

(2022) PROCEEDINGS OF MACHINE LEARNING RESEARCH. 198.
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Introduction to the special section on AI in manufacturing : current trends and challenges

Jefrey Lijffijt (UGent) , Dimitra Gkorou, Pieter Van Hertum, Alexander Ypma, Mykola Pechenizkiy and Joaquin Vanschoren

(2022) SIGKDD EXPLORATIONS. 24(2). p.81-85
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Evaluating representation learning and graph layout methods for visualization

Edith Heiter (UGent) , Bo Kang (UGent) , Tijl De Bie (UGent) and Jefrey Lijffijt (UGent)

(2022) IEEE COMPUTER GRAPHICS AND APPLICATIONS. 42(3). p.19-28
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Topologically regularized data embeddings

Robin Vandaele, Bo Kang (UGent) , Jefrey Lijffijt (UGent) , Tijl De Bie (UGent) and Yvan Saeys (UGent)

(2022) International Conference on Learning Representations (ICLR 2022), Proceedings.

Academic Bibliography

Exploring the performance of continuous-time dynamic link prediction algorithms

Scalable job recommendation with lower congestion using optimal transport

FEIR : quantifying and reducing envy and inferiority for fair recommendation of limited resources

GREASE : graph imbalance reduction by adding sets of edges

Pattern or artifact? Interactively exploring embedding quality with TRACE

Incorporating topological priors into low-dimensional visualizations through topological regularization

A challenge-based survey of e-recruitment recommendation systems

Large language models reflect the ideology of their creators

An empirical evaluation of network representation learning methods

Gaussian embedding of temporal networks

FEIR : quantifying and reducing envy and inferiority for fair recommendation of limited resources

Revised conditional t-SNE : looking beyond the nearest neighbors

ReCon : reducing congestion in job recommendation using optimal transport

Topologically regularized data embeddings

EvalNE : a framework for network embedding evaluation

A challenge-based survey of e-recruitment recommendation systems

A systematic evaluation of node embedding robustness

Introduction to the special section on AI in manufacturing : current trends and challenges

Evaluating representation learning and graph layout methods for visualization

Topologically regularized data embeddings

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