Bart Goethals

发表

On Private Scalar Product Computation for Privacy-Preserving Data Mining

Bart Goethals, Taneli Mielikäinen, Sven Laur, 2004, ICISC.

Automatic Vandalism Detection in Wikipedia : Towards a Machine Learning Approach

Bart Goethals, Koen Smets, B. Verdonk, 2008 .

Mining Non-Derivable Association Rules

Bart Goethals, Hannu Toivonen, Juho Muhonen, 2005, SDM.

Automatic Abstracting

Luciano Baresi, Philippe Bonnet, Bernhard Thalheim, 2009, Encyclopedia of Database Systems.

What You Store Is What You Get ( extended abstract )

Floris Geerts, Bart Goethals, Taneli Mielikäinen, 2003 .

BioGraph: unsupervised biomedical knowledge discovery via automated hypothesis generation

A. Liekens, Bart Goethals, Walter Daelemans, 2011, Genome Biology.

Visual Interactive Neighborhood Mining on High Dimensional Data

Bart Goethals, Emmanuel Müller, Emin Aksehirli, 2015 .

Adaptive Database Replication

Luciano Baresi, Ioana Manolescu, Philip S. Yu, 2009, Encyclopedia of Database Systems.

Audio Feature Extraction

Luciano Baresi, Philippe Bonnet, Bernhard Thalheim, 2009, Encyclopedia of Database Systems.

Adversarial Information Retrieval

Luciano Baresi, Philippe Bonnet, Bernhard Thalheim, 2009, Encyclopedia of Database Systems.

Proceedings of the SIAM International Conference on Data Mining, SDM 2010, April 29 - May 1, 2010, Columbus, Ohio, USA

Bart Goethals, J. Pei, J. Pei, 2010, SDM.

Fleet-Oriented Pattern Mining Combined with Time Series Signature Extraction for Understanding of Wind Farm Response to Storm Conditions

T. Verstraeten, J. Helsen, Bart Goethals, 2021 .

Determining the Presence of Political Parties in Social Circles

M. de Rijke, Maarten de Rijke, Bart Goethals, 2015, ICWSM.

Searching for patterns in long sequences

C. Blondia, Bart Goethals, B. Cule, 2012 .

Proceedings of the 12th IEEE International Conference on Data Mining Workshops (ICDMW), IEEE, 2012

Geoffrey I. Webb, Bart Goethals, Jeffrey Xu Yu, 2012 .

Embarrassingly shallow auto-encoders for dynamic collaborative filtering

Bart Goethals, Olivier Jeunen, Jan Van Balen, 2022, User Modeling and User-Adapted Interaction.

Proceedings of the ICDM 2003 Workshop on Frequent Itemset Mining Implementations (FIMI'03)

Bart Goethals, Mohammed J. Zaki, Bart Goethals, 2003 .

ICDMW 2012 : the 12th IEEE International Conference on Data Mining Workshops, Brussels, Belgium, December 10, 2012

Xindong Wu, Bart Goethals, Jeffrey Xu Yu, 2012 .

Proceedings of the ACM SIGKDD Open Source Data Mining Workshop

Bart Goethals, Mohammed J. Zaki, Siegfried Nijssen, 2005 .

FIMI '04, Proceedings of the IEEE ICDM Workshop on Frequent Itemset Mining Implementations, Brighton, UK, November 1, 2004

Bart Goethals, Roberto J. Bayardo, Mohammed J. Zaki, 2004, FIMI.

Proceedings of the IEEE ICDM Workshop on Frequent Itemset Mining Implementations (FIMI 2004)

Bart Goethals, Mohammed J. Zaki, R. Bayardo, 2004 .

FIMI '03, Frequent Itemset Mining Implementations, Proceedings of the ICDM 2003 Workshop on Frequent Itemset Mining Implementations, 19 December 2003, Melbourne, Florida, USA

Bart Goethals, Mohammed J. Zaki, Bart Goethals, 2003, FIMI.

Mining frequent itemsets in a stream

Joris J. M. Gillis, Bart Goethals, T. Calders, 2014, Inf. Syst..

ICDM 2012 : the 12th IEEE International Conference on Data Mining, Brussels, Belgium, December 10-13, 2012

Mohammed J. Zaki, Xindong Wu, J. Yu, 2012 .

Modelling Users with Item Metadata for Explainable and Interactive Recommendation

Joey De Pauw, Bart Goethals, J. D. Pauw, 2022, ArXiv.

Adaptive Metric Techniques

Luciano Baresi, Ioana Manolescu, Philip S. Yu, 2009, Encyclopedia of Database Systems.

What Are Filter Bubbles Really? A Review of the Conceptual and Empirical Work

Bart Goethals, Annelien Smets, L. Michiels, 2022, UMAP.

Finding interesting queries in relational databases

Bart Goethals, Bart Goethals, 2007, EGC.

Minimal k-free representations

Toon Calders, Bart Goethals, Bart Goethals, 2003 .

Who do you think I am? Interactive User Modelling with Item Metadata

Bart Goethals, Joey De Pauw, Koen Ruymbeek, 2022, RecSys.

Pessimistic Decision-Making for Recommender Systems

Bart Goethals, Olivier Jeunen, 2022, ACM Transactions on Recommender Systems.

Proceedings of the 2010 SIAM International Conference on Data Mining

Srinivasan Parthasarathy, Jian Pei, Bart Goethals, 2010 .

Proceedings of the ECML PKDD workshop on instant interactive data mining

Bart Goethals, Anton Dries, Siegfried Nijssen, 2012 .

Are We Forgetting Something? Correctly Evaluate a Recommender System With an Optimal Training Window

Bart Goethals, L. Michiels, Robin Verachtert, 2022, Perspectives@RecSys.

Analyzing concept drift and shift from sample data

Geoffrey I. Webb, Loong Kuan Lee, Bart Goethals, 2018, Data Mining and Knowledge Discovery.

An inductive database system based on virtual mining views

H. Blockeel, C. Robardet, Bart Goethals, 2011, Data Mining and Knowledge Discovery.

Frequent Itemset Mining for Big Data

Bart Goethals, Sandy Moens, Emin Aksehirli, 2013, 2013 IEEE International Conference on Big Data.

Protein complex analysis: From raw protein lists to protein interaction networks.

Lennart Martens, Bart Goethals, Jan Tavernier, 2017, Mass spectrometry reviews.

A primer to frequent itemset mining for bioinformatics

Bart Goethals, Wout Bittremieux, Kris Laukens, 2013, Briefings Bioinform..

k-Morik: Mining Patterns to Classify Cartified Images of Katharina

Bart Goethals, Élisa Fromont, Bart Goethals, 2016, Solving Large Scale Learning Tasks.

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

Bart Goethals, Mohammed J. Zaki, Bart Goethals, 2004, SKDD.

Identifying and characterising anomalies in data

Bart Goethals, Jan Paredaens, Koen Smets, 2012 .

Grasping frequent subgraph mining for bioinformatics applications

Boris Cule, Bart Goethals, Wout Bittremieux, 2018, BioData Mining.

Mining the entire Protein DataBank for frequent spatially cohesive amino acid patterns

Boris Cule, Bart Goethals, Cheng Zhou, 2015, BioData Mining.

Survey on Frequent Pattern Mining

Bart Goethals, Bart Goethals, 2003 .

Collaborative Filtering for Binary, Positiveonly Data

Boris Cule, Bart Goethals, Kanishka Bhaduri, 2017, SKDD.

A priori versus a posteriori filtering of association rules

Bart Goethals, Jan Van den Bussche, J. Bussche, 1999, 1999 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery.

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

Geoffrey I. Webb, Bart Goethals, Ahmed Shifaz, 2018, Data Mining and Knowledge Discovery.

Top-K Contextual Bandits with Equity of Exposure

Bart Goethals, Olivier Jeunen, Bart Goethals, 2021, RecSys.

Relational Association Rules: Getting WARMeR

Bart Goethals, Jan Van den Bussche, J. Bussche, 2002, Pattern Detection and Discovery.

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

Geert Wets, Tom Brijs, Koen Vanhoof, 2000, KDD '00.

PETSC: pattern-based embedding for time series classification

Bart Goethals, B. Cule, Len Feremans, 2022, Data Mining and Knowledge Discovery.

Efficient Cluster Detection by Ordered Neighborhoods

Bart Goethals, Emmanuel Müller, Emin Aksehirli, 2015, DaWaK.

Mining rank-correlated sets of numerical attributes

Szymon Jaroszewicz, Toon Calders, Bart Goethals, 2006, KDD '06.

Mining Cohesive Itemsets in Graphs

Boris Cule, Bart Goethals, Tayena Hendrickx, 2014, Discovery Science.

Mining Interesting Itemsets in Graph Datasets

Boris Cule, Bart Goethals, Tayena Hendrickx, 2013, PAKDD.

Mining tree queries in a graph

Bart Goethals, Jan Van den Bussche, Eveline Hoekx, 2005, KDD '05.

OSDM 2005 Proceedings of the First International Workshop on Open Source Data Mining

Bart Goethals, Mohammed J. Zaki, Siegfried Nijssen, 2005 .

Providing Concise Database Covers Instantly by Recursive Tile Sampling

Bart Goethals, Mario Boley, Sandy Moens, 2014, Discovery Science.

Efficient frequent pattern mining

Bart Goethals, Bart Goethals, 2002 .

Interactive Constrained Association Rule Mining

Bart Goethals, Jan Van den Bussche, J. Bussche, 2001, ArXiv.

On Supporting Interactive Association Rule Mining

Bart Goethals, Jan Van den Bussche, J. Bussche, 2000, DaWaK.

Mining interesting sets and rules in relational databases

Bart Goethals, Michael Mampaey, Wim Le Page, 2010, SAC '10.

Efficient pattern-based anomaly detection in a network of multivariate devices

Bart Goethals, B. Cule, Len Feremans, 2023, ArXiv.

A Neighbourhood-based Location- and Time-aware Recommender System

Bart Goethals, Robin Verachtert, Len Feremans, 2022, ORSUM@RecSys.

Cleaning Data with Forbidden Itemsets

Bart Goethals, Floris Geerts, Joeri Rammelaere, 2017, 2017 IEEE 33rd International Conference on Data Engineering (ICDE).

Tiling Databases

Bart Goethals, Taneli Mielikäinen, Floris Geerts, 2004, Discovery Science.

Analyzing concept drift and shift from sample data

Geoffrey I. Webb, Bart Goethals, François Petitjean, 2018, Data Mining and Knowledge Discovery.

Machine Learning and Knowledge Discovery in Databases, European Conference, ECML/PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I

Katharina Morik, Walter Daelemans, Bart Goethals, 2008, ECML/PKDD.

Understanding Concept Drift pdf

Geoffrey I. Webb, Bart Goethals, François Petitjean, 2017, ArXiv.

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

Bart Goethals, Dirk Valkenborg, Filip Lemière, 2011, BMC Bioinformatics.

Efficiently mining cohesion-based patterns and rules in event sequences

Bart Goethals, B. Cule, Len Feremans, 2019, Data Mining and Knowledge Discovery.

Efficient Discovery of Sets of Co-occurring Items in Event Sequences

Len Feremans, Boris Cule, Bart Goethals, 2016, ECML/PKDD.

Approximation of Frequentness Probability of Itemsets in Uncertain Data

Toon Calders, Bart Goethals, Calin Garboni, 2010, 2010 IEEE International Conference on Data Mining.

Efficient Pattern Mining of Uncertain Data with Sampling

Toon Calders, Bart Goethals, Calin Garboni, 2010, PAKDD.

Memory issues in frequent itemset mining

Bart Goethals, Bart Goethals, 2004, SAC '04.

Frequent Set Mining

Bart Goethals, Bart Goethals, 2010, Data Mining and Knowledge Discovery Handbook.

Depth-First Non-Derivable Itemset Mining

Toon Calders, Bart Goethals, Bart Goethals, 2005, SDM.

MARBLES: Mining association rules buried in long event sequences

Boris Cule, Bart Goethals, Nikolaj Tatti, 2012, Stat. Anal. Data Min..

Mining Association Rules in Long Sequences

Boris Cule, Bart Goethals, Bart Goethals, 2010, PAKDD.

A New Constraint for Mining Sets in Sequences

Céline Robardet, Boris Cule, Bart Goethals, 2009, SDM.

Mining Top-k Quantile-based Cohesive Sequential Patterns

Len Feremans, Boris Cule, Bart Goethals, 2018, SDM.

Advances in Frequent Itemset Mining Implementations: Introduction to FIMI03

Bart Goethals, Mohammed J. Zaki, Bart Goethals, 2003, FIMI.

ClaSP: An Efficient Algorithm for Mining Frequent Closed Sequences

Roque Marín, Manuel Campos, Antonio Gomariz, 2013, PAKDD.

Mining Frequent Itemsets in a Stream

Toon Calders, Bart Goethals, Nele Dexters, 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).

Non-derivable itemset mining

Toon Calders, Bart Goethals, Bart Goethals, 2007, Data Mining and Knowledge Discovery.

MIME: a framework for interactive visual pattern mining

Bart Goethals, Jilles Vreeken, Sandy Moens, 2011, KDD.

Mining All Non-derivable Frequent Itemsets

Toon Calders, Bart Goethals, Bart Goethals, 2002, PKDD.

Mining Views: Database Views for Data Mining

Toon Calders, Bart Goethals, Hendrik Blockeel, 2008, 2008 IEEE 24th International Conference on Data Engineering.

Predicting the severity of a reported bug

Bart Goethals, Serge Demeyer, Emanuel Giger, 2010, 2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010).

FP-Bonsai: The Art of Growing and Pruning Small FP-Trees

Bart Goethals, Francesco Bonchi, F. Bonchi, 2004, PAKDD.

Scheduling on a budget: Avoiding stale recommendations with timely updates

Bart Goethals, Olivier Jeunen, Robin Verachtert, 2023, Machine Learning with Applications.

A Framework for Pattern Mining and Anomaly Detection in Multi-dimensional Time Series and Event Logs

Len Feremans, Vincent Vercruyssen, Boris Cule, 2019, NFMCP@PKDD/ECML.

Apriori Property and Breadth-First Search Algorithms

Bart Goethals, Bart Goethals, 2009, Encyclopedia of Database Systems.

Combining instance and feature neighbours for extreme multi-label classification

Bart Goethals, C. Vens, B. Cule, 2020, International Journal of Data Science and Analytics.

Audit Trail

Luciano Baresi, Ioana Manolescu, Vilém Novák, 2020, Encyclopedia of Database Systems.

Itemset Based Sequence Classification

Boris Cule, Bart Goethals, Cheng Zhou, 2013, ECML/PKDD.

RASCL: a randomised approach to subspace clusters

Bart Goethals, B. Cule, Sandy Moens, 2022, International Journal of Data Science and Analytics.

Pattern Based Sequence Classification

Boris Cule, Bart Goethals, Cheng Zhou, 2016, IEEE Transactions on Knowledge and Data Engineering.

Cohesion based co-location pattern mining

Boris Cule, Bart Goethals, Cheng Zhou, 2015, 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

Mining spatially cohesive itemsets in protein molecular structures

Boris Cule, Bart Goethals, Cheng Zhou, 2013, BioKDD '13.

Inductive Querying with Virtual Mining Views

Bart Goethals, Hendrik Blockeel, Élisa Fromont, 2010, Inductive Databases and Constraint-Based Data Mining.

An inductive database prototype based on virtual mining views

Hendrik Blockeel, Bart Goethals, Céline Robardet, 2008, KDD.

Integrating Pattern Mining in Relational Databases

Toon Calders, Bart Goethals, Adriana Prado, 2006, PKDD.

Quick Inclusion-Exclusion

Toon Calders, Bart Goethals, Bart Goethals, 2005, KDID.

A tight upper bound on the number of candidate patterns

Bart Goethals, Jan Van den Bussche, Floris Geerts, 2001, Proceedings 2001 IEEE International Conference on Data Mining.

Summarizing Data with Informative Patterns

Bart Goethals, Michael Mampaey, Bart Goethals, 2011 .

FIMI'03: Workshop on Frequent Itemset Mining Implementations

Bart Goethals, Mohammed J. Zaki, Bart Goethals, 2003 .

Pessimistic Reward Models for Off-Policy Learning in Recommendation

Bart Goethals, Olivier Jeunen, Bart Goethals, 2021, RecSys.

Pattern-Based Anomaly Detection in Mixed-Type Time Series

Len Feremans, Vincent Vercruyssen, Boris Cule, 2019, ECML/PKDD.

Unifying nearest neighbors collaborative filtering

Bart Goethals, Koen Verstrepen, Bart Goethals, 2014, RecSys '14.

Pessimistic Decision-Making for Recommender Systems

Bart Goethals, Olivier Jeunen, 2022, Trans. Recomm. Syst..

Mining Train Delays

Boris Cule, Bart Goethals, Sabine Verboven, 2011, IDA.

Mining Association Rules of Simple Conjunctive Queries

Bart Goethals, Heikki Mannila, Wim Le Page, 2008, SDM.

Machine learning and knowledge discovery in databases : European conference, ECML PKDD 2008, Antwerp, Belgium, September 15-19, 2008 : proceedings

Katharina Morik, Walter Daelemans, Bart Goethals, 2008, PKDD 2008.

Closed-Form Models for Collaborative Filtering with Side-Information

Bart Goethals, J. V. Balen, Olivier Jeunen, 2020, RecSys.

Practical Approaches for Mining Frequent Patterns in Molecular Datasets

Bart Goethals, Kris Laukens, Sandy Moens, 2016, Bioinformatics and biology insights.

Mining Association Rules in Graphs Based on Frequent Cohesive Itemsets

Boris Cule, Bart Goethals, Kris Laukens, 2015, PAKDD.

An inductive database system based on virtual mining views

H. Blockeel, C. Robardet, Bart Goethals, 2011, Data Mining and Knowledge Discovery.

BioGraph: Knowledge Discovery and Exploration in the Biomedical Domain

Walter Daelemans, Bart Goethals, Jeroen De Knijf, 2011, 2011 IEEE 11th International Conference on Data Mining Workshops.

Efficient reduction of candidate matches in peptide spectrum library searching using the top k most intense peaks.

Bart Goethals, Wout Bittremieux, Trung Nghia Vu, 2014, Journal of proteome research.

Assigning clinical codes with data-driven concept representation on Dutch clinical free text

Walter Daelemans, Bart Goethals, Kim Luyckx, 2017, J. Biomed. Informatics.

Fair offline evaluation methodologies for implicit-feedback recommender systems with MNAR data

Bart Goethals, Koen Verstrepen, Olivier Jeunen, 2018 .

RecPack: An(other) Experimentation Toolkit for Top-N Recommendation using Implicit Feedback Data

Bart Goethals, L. Michiels, Robin Verachtert, 2022, RecSys.

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

Kim A. Verwaest, Bart Goethals, A. Verschoren, 2011, BMC Bioinformatics.

Providing concise database covers using recursive tile sampling

Bart Goethals, Mario Boley, Sandy Moens, 2014, IFIP Working Conference on Database Semantics.

Audit Trail

Eric C. Jensen, K. A. Ross, Philip S. Yu, 2020, Definitions.