World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
7473
World Ranking
8012
National Ranking
80

Overview

Bart Goethals is affiliated with the University of Antwerp in Belgium and conducts research primarily in the field of Computer Science, with a focus on Artificial Intelligence, Information Systems, and related subfields.

The scientist's work spans several specialized areas including:

  • Recommender Systems and Techniques
  • Advanced Bandit Algorithms Research
  • Data Mining Algorithms and Applications
  • Time Series Analysis and Forecasting
  • Anomaly Detection Techniques and Applications
  • Data Stream Mining Techniques
  • Data Management and Algorithms

Bart Goethals has contributed to a variety of research publications in notable venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • ACM Transactions on Recommender Systems
  • International Journal of Data Science and Analytics
  • Data Mining and Knowledge Discovery
  • Proceedings of the International AAAI Conference on Web and Social Media

Recent papers authored or co-authored by the scientist include:

  • "PETSC: pattern-based embedding for time series classification" (2022), published in Data Mining and Knowledge Discovery
  • "Pessimistic Decision-Making for Recommender Systems" (2022), published in ACM Transactions on Recommender Systems
  • "Embarrassingly shallow auto-encoders for dynamic collaborative filtering" (2022), published in User Modeling and User-Adapted Interaction
  • "Determining the Presence of Political Parties in Social Circles" (2021), published in Proceedings of the International AAAI Conference on Web and Social Media
  • "A Framework and Toolkit for Testing the Correctness of Recommendation Algorithms" (2023), published in ACM Transactions on Recommender Systems

The scientist has collaborated frequently with several co-authors, including:

  • Boris Čule (8 collaborations)
  • Len Feremans (7 collaborations)
  • Olivier Jeunen (3 collaborations)
  • Robin Verachtert (3 collaborations)
  • Joey De Pauw (3 collaborations)

Bart Goethals has also authored a book titled Artificial Intelligence and Machine Learning, published by Springer Science+Business Media in 2023.

Best Publications

  • On private scalar product computation for privacy-preserving data mining

    Bart Goethals;Sven Laur;Helger Lipmaa;Taneli Mielikäinen

  • Predicting the severity of a reported bug

    Ahmed Lamkanfi;Serge Demeyer;Emanuel Giger;Bart Goethals

  • Mining All Non-derivable Frequent Itemsets

    Toon Calders;Bart Goethals

  • Survey on Frequent Pattern Mining

    Bart Goethals

  • Frequent Itemset Mining for Big Data

    Sandy Moens;Emin Aksehirli;Bart Goethals

  • Proximity forest: an effective and scalable distance-based classifier for time series

    Benjamin Lucas;Ahmed Shifaz;Charlotte Pelletier;Lachlan O'Neill

  • Tiling Databases

    Unknown

  • Advances in frequent itemset mining implementations: report on FIMI'03

    Bart Goethals;Mohammed J. Zaki

  • Non-derivable itemset mining

    Toon Calders;Bart Goethals

  • ClaSP: An Efficient Algorithm for Mining Frequent Closed Sequences

    Antonio Gomariz;Manuel Campos;Roque Marin;Bart Goethals

  • A primer to frequent itemset mining for bioinformatics

    Stefan Naulaerts;Pieter Meysman;Wout Bittremieux;Trung Nghia Vu

  • BioGraph: unsupervised biomedical knowledge discovery via automated hypothesis generation

    Anthony M L Liekens;Jeroen De Knijf;Walter Daelemans;Bart Goethals

  • Advances in Frequent Itemset Mining Implementations: Introduction to FIMI03.

    Bart Goethals;Mohammed Javeed Zaki

  • Mining frequent itemsets in a stream

    Toon Calders;Nele Dexters;Joris J. M. Gillis;Bart Goethals

  • Frequent Set Mining

    Bart Goethals

  • A data mining framework for optimal product selection in retail supermarket data: the generalized PROFSET model

    Tom Brijs;Bart Goethals;Gilbert Swinnen;Koen Vanhoof

  • Knowledge Discovery in Inductive Databases

    Bart Goethals;Arno Siebes

  • Analyzing concept drift and shift from sample data

    Geoffrey I. Webb;Loong Kuan Lee;Bart Goethals;Bart Goethals;François Petitjean

  • Proceedings of the SIAM International Conference on Data Mining (SDM)

    B. Goethals;J. Pei

  • Unifying nearest neighbors collaborative filtering

    Koen Verstrepen;Bart Goethals

  • Approximation of Frequentness Probability of Itemsets in Uncertain Data

    Toon Calders;Calin Garboni;Bart Goethals

  • An integrated workflow for robust alignment and simplified quantitative analysis of NMR spectrometry data.

    Trung-Nghia Vu;Dirk Valkenborg;Dirk Valkenborg;Koen Smets;Kim A. Verwaest

Frequent Co-Authors

Toon Calders
Toon Calders University of Antwerp
Mohammed J. Zaki
Mohammed J. Zaki Rensselaer Polytechnic Institute
Jilles Vreeken
Jilles Vreeken Max Planck Society
Jan Van den Bussche
Jan Van den Bussche Hasselt University
Siegfried Nijssen
Siegfried Nijssen Université Catholique de Louvain
Walter Daelemans
Walter Daelemans University of Antwerp
Geoffrey I. Webb
Geoffrey I. Webb Monash University
Floris Geerts
Floris Geerts University of Antwerp
Jurgen Del-Favero
Jurgen Del-Favero University of Antwerp

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