Jefrey Lijffijt

114 papers A* 7A 5B 9Journal 61Unranked 24
YearRankTypeTitle / Venue / Authors
2026 J jnl
How Predicted Links Influence Network Evolution: Disentangling Choice and Algorithmic Feedback in Dynamic Graphs.
CoRR
Mathilde Perez, Raphaël Romero, Jefrey Lijffijt, Charlotte Laclau
2025 J jnl
Are LLMs ready to help non-expert users to make charts of official statistics data?
CoRR
Gadir Suleymanli, Alexander Rogiers, Lucas Lageweg, Jefrey Lijffijt
2025 J jnl
BiMi Sheets: Infosheets for bias mitigation methods.
CoRR
MaryBeth Defrance, Guillaume Bied, Maarten Buyl, Jefrey Lijffijt, Tijl De Bie
2025 — conf
InfoClus: Informative Clustering of High-Dimensional Data Embeddings.
ECML/PKDD (1)
Fuyin Lai, Edith Heiter, Guillaume Bied, Jefrey Lijffijt
2025 J jnl
InfoClus: Informative Clustering of High-dimensional Data Embeddings.
CoRR
Fuyin Lai, Edith Heiter, Guillaume Bied, Jefrey Lijffijt
2025 J jnl
SimHawNet: a modified Hawkes process for temporal network simulation.
Data Min. Knowl. Discov.
Mathilde Perez, Raphaël Romero, Bo Kang, Tijl De Bie, Jefrey Lijffijt, Charlotte Laclau
2025 — conf
What Large Language Models Do Not Talk About: An Empirical Study of Moderation and Censorship Practices.
ECML/PKDD (1)
Sander Noels, Guillaume Bied, Maarten Buyl, Alexander Rogiers, Yousra Fettach, Jefrey Lijffijt, Tijl De Bie
2025 J jnl
What Large Language Models Do Not Talk About: An Empirical Study of Moderation and Censorship Practices.
CoRR
Sander Noels, Guillaume Bied, Maarten Buyl, Alexander Rogiers, Yousra Fettach, Jefrey Lijffijt, Tijl De Bie
2024 J jnl
A Challenge-based Survey of E-recruitment Recommendation Systems.
ACM Comput. Surv.
Yoosof Mashayekhi, Nan Li, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2024 J jnl
An Empirical Evaluation of Network Representation Learning Methods.
Big Data
Alexandru Cristian Mara, Jefrey Lijffijt, Tijl De Bie
2024 J jnl
Exploring the Performance of Continuous-Time Dynamic Link Prediction Algorithms.
CoRR
Raphaël Romero, Maarten Buyl, Tijl De Bie, Jefrey Lijffijt
2024 J jnl
FEIR: Quantifying and Reducing Envy and Inferiority for Fair Recommendation of Limited Resources.
ACM Trans. Intell. Syst. Technol.
Nan Li, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2024 J jnl
GREASE: Graph Imbalance Reduction by Adding Sets of Edges.
IEEE Trans. Knowl. Data Eng.
Yoosof Mashayekhi, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2024 J jnl
Gaussian Embedding of Temporal Networks.
CoRR
Raphaël Romero, Jefrey Lijffijt, Riccardo Rastelli, Marco Corneli, Tijl De Bie
2024 J jnl
Incorporating Topological Priors Into Low-Dimensional Visualizations Through Topological Regularization.
IEEE Access
Edith Heiter, Robin Vandaele, Tijl De Bie, Yvan Saeys, Jefrey Lijffijt
2024 J jnl
Large Language Models Reflect the Ideology of their Creators.
CoRR
Maarten Buyl, Alexander Rogiers, Sander Noels, Iris Dominguez-Catena, Edith Heiter, Raphaël Romero, Iman Johary, Alexandru Cristian Mara, Jefrey Lijffijt, Tijl De Bie
2024 — conf
Pattern or Artifact? Interactively Exploring Embedding Quality with TRACE.
ECML/PKDD (8)
Edith Heiter, Liesbet Martens, Ruth Seurinck, Martin Guilliams, Tijl De Bie, Yvan Saeys, Jefrey Lijffijt
2024 J jnl
Pattern or Artifact? Interactively Exploring Embedding Quality with TRACE.
CoRR
Edith Heiter, Liesbet Martens, Ruth Seurinck, Martin Guilliams, Tijl De Bie, Yvan Saeys, Jefrey Lijffijt
2024 J jnl
Scalable Job Recommendation With Lower Congestion Using Optimal Transport.
IEEE Access
Yoosof Mashayekhi, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2023 — ed.
Artificial Intelligence and Machine Learning - 34th Joint Benelux Conference, BNAIC/Benelearn 2022, Mechelen, Belgium, November 7-9, 2022, Revised Selected Papers
BNAIC/BENELEARN
Toon Calders, Celine Vens, Jefrey Lijffijt, Bart Goethals
2023 — conf
FEIR: Quantifying and Reducing Envy and Inferiority for Fair Recommendation of Limited Resources.
HR@RecSys
Nan Li, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2023 J jnl
FEIR: Quantifying and Reducing Envy and Inferiority for Fair Recommendation of Limited Resources.
CoRR
Nan Li, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2023 J jnl
Gaussian Embedding of Temporal Networks.
IEEE Access
Raphaël Romero, Jefrey Lijffijt, Riccardo Rastelli, Marco Corneli, Tijl De Bie
2023 J jnl
New Perspectives on the Evaluation of Link Prediction Algorithms for Dynamic Graphs.
CoRR
Raphaël Romero, Tijl De Bie, Jefrey Lijffijt
2023 A conf
ReCon: Reducing Congestion in Job Recommendation using Optimal Transport.
RecSys
Yoosof Mashayekhi, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2023 J jnl
ReCon: Reducing Congestion in Job Recommendation using Optimal Transport.
CoRR
Yoosof Mashayekhi, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2023 B conf
Revised Conditional t-SNE: Looking Beyond the Nearest Neighbors.
IDA
Edith Heiter, Bo Kang, Ruth Seurinck, Jefrey Lijffijt
2023 J jnl
Revised Conditional t-SNE: Looking Beyond the Nearest Neighbors.
CoRR
Edith Heiter, Bo Kang, Ruth Seurinck, Jefrey Lijffijt
2023 J jnl
Topologically Regularized Data Embeddings.
CoRR
Edith Heiter, Robin Vandaele, Tijl De Bie, Yvan Saeys, Jefrey Lijffijt
2022 — conf
A Systematic Evaluation of Node Embedding Robustness.
LoG
Alexandru Cristian Mara, Jefrey Lijffijt, Stephan Günnemann, Tijl De Bie
2022 J jnl
A Systematic Evaluation of Node Embedding Robustness.
CoRR
Alexandru Mara, Jefrey Lijffijt, Stephan Günnemann, Tijl De Bie
2022 J jnl
A challenge-based survey of e-recruitment recommendation systems.
CoRR
Yoosof Mashayekhi, Nan Li, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2022 J jnl
EvalNE: A framework for network embedding evaluation.
SoftwareX
Alexandru Mara, Jefrey Lijffijt, Tijl De Bie
2022 J jnl
Evaluating Representation Learning and Graph Layout Methods for Visualization.
IEEE Computer Graphics and Applications
Edith Heiter, Bo Kang, Tijl De Bie, Jefrey Lijffijt
2022 J jnl
Introduction to the Special Section on AI in Manufacturing: Current Trends and Challenges.
SIGKDD Explor.
Jefrey Lijffijt, Dimitra Gkorou, Pieter Van Hertum, Alexander Ypma, Mykola Pechenizkiy, Joaquin Vanschoren
2022 A* conf
Topologically Regularized Data Embeddings.
ICLR
Robin Vandaele, Bo Kang, Jefrey Lijffijt, Tijl De Bie, Yvan Saeys
2021 — conf
Adversarial Robustness of Probabilistic Network Embedding for Link Prediction.
PKDD/ECML Workshops (2)
Xi Chen, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2021 J jnl
Adversarial Robustness of Probabilistic Network Embedding for Link Prediction.
CoRR
Xi Chen, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2021 — ed.
Artificial Intelligence and Machine Learning - 32nd Benelux Conference, BNAIC/Benelearn 2020, Leiden, The Netherlands, November 19-20, 2020, Revised Selected Papers
BNAIC/BENELEARN (Selected Papers)
Mitra Baratchi, Lu Cao, Walter A. Kosters, Jefrey Lijffijt, Jan N. van Rijn, Frank W. Takes
2021 B conf
Conditional t-SNE: More informative t-SNE embeddings.
DSAA
Bo Kang, Dario García-García, Jefrey Lijffijt, Raúl Santos-Rodríguez, Tijl De Bie
2021 J jnl
Conditional t-SNE: more informative t-SNE embeddings.
Mach. Learn.
Bo Kang, Dario García-García, Jefrey Lijffijt, Raúl Santos-Rodríguez, Tijl De Bie
2021 J jnl
ExClus: Explainable Clustering on Low-dimensional Data Representations.
CoRR
Xander Vankwikelberge, Bo Kang, Edith Heiter, Jefrey Lijffijt
2021 — conf
Explanations for Network Embedding-Based Link Predictions.
PKDD/ECML Workshops (1)
Bo Kang, Jefrey Lijffijt, Tijl De Bie
2021 — ed.
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part I
ECML/PKDD (1)
Frank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera
2021 — ed.
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part II
ECML/PKDD (2)
Frank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera
2021 — ed.
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part III
PKDD/ECML (3)
Frank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera
2021 — ed.
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I
PKDD/ECML Workshops (1)
Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça
2021 — ed.
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II
PKDD/ECML Workshops (2)
Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça
2021 J jnl
Mining explainable local and global subgraph patterns with surprising densities.
Data Min. Knowl. Discov.
Junning Deng, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2021 — conf
Quantifying and Reducing Imbalance in Networks.
HR@RecSys
Yoosof Mashayekhi, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2021 J jnl
Topologically Regularized Data Embeddings.
CoRR
Robin Vandaele, Bo Kang, Jefrey Lijffijt, Tijl De Bie, Yvan Saeys
2020 J jnl
A Constrained Randomization Approach to Interactive Visual Data Exploration with Subjective Feedback.
IEEE Trans. Knowl. Data Eng.
Bo Kang, Kai Puolamäki, Jefrey Lijffijt, Tijl De Bie
2020 J jnl
ALPINE: Active Link Prediction using Network Embedding.
CoRR
Xi Chen, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2020 B conf
Benchmarking Network Embedding Models for Link Prediction: Are We Making Progress?
DSAA
Alexandru Cristian Mara, Jefrey Lijffijt, Tijl De Bie
2020 B conf
Block-Approximated Exponential Random Graphs.
DSAA
Florian Adriaens, Alexandru Mara, Jefrey Lijffijt, Tijl De Bie
2020 A conf
CSNE: Conditional Signed Network Embedding.
CIKM
Alexandru Mara, Yoosof Mashayekhi, Jefrey Lijffijt, Tijl De Bie
2020 J jnl
CSNE: Conditional Signed Network Embedding.
CoRR
Alexandru Mara, Yoosof Mashayekhi, Jefrey Lijffijt, Tijl De Bie
2020 A conf
Explainable Subgraphs with Surprising Densities: A Subgroup Discovery Approach.
SDM
Junning Deng, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2020 J jnl
Explainable Subgraphs with Surprising Densities: A Subgroup Discovery Approach.
CoRR
Junning Deng, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2020 J jnl
FONDUE: A Framework for Node Disambiguation Using Network Embeddings.
CoRR
Ahmad Mel, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2020 B conf
FONDUE: Framework for Node Disambiguation Using Network Embeddings.
DSAA
Ahmad Mel, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2020 B conf
Gibbs Sampling Subjectively Interesting Tiles.
IDA
Anes Bendimerad, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie
2020 J jnl
Interactive visual data exploration with subjective feedback: an information-theoretic approach.
Data Min. Knowl. Discov.
Kai Puolamäki, Emilia Oikarinen, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2020 J jnl
Network Representation Learning for Link Prediction: Are we improving upon simple heuristics?
CoRR
Alexandru Mara, Jefrey Lijffijt, Tijl De Bie
2020 J jnl
Relaxing the strong triadic closure problem for edge strength inference.
Data Min. Knowl. Discov.
Florian Adriaens, Tijl De Bie, Aristides Gionis, Jefrey Lijffijt, Antonis Matakos, Polina Rozenshtein
2020 J jnl
SIAS-miner: mining subjectively interesting attributed subgraphs.
Data Min. Knowl. Discov.
Anes Bendimerad, Ahmad Mel, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie
2020 J jnl
Scalable Dyadic Independence Models with Local and Global Constraints.
CoRR
Florian Adriaens, Alexandru Mara, Jefrey Lijffijt, Tijl De Bie
2019 — conf
Conditional Network Embeddings.
BNAIC/BENELEARN
Bo Kang, Jefrey Lijffijt, Tijl De Bie
2019 — conf
Conditional Network Embeddings.
ICLR (Poster)
Bo Kang, Jefrey Lijffijt, Tijl De Bie
2019 J jnl
Conditional t-SNE: Complementary t-SNE embeddings through factoring out prior information.
CoRR
Bo Kang, Dario García-García, Jefrey Lijffijt, Raúl Santos-Rodríguez, Tijl De Bie
2019 A* conf
Contrastive Antichains in Hierarchies.
KDD
Anes Bendimerad, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie
2019 A conf
Discovering Interesting Cycles in Directed Graphs.
CIKM
Florian Adriaens, Çigdem Aslay, Tijl De Bie, Aristides Gionis, Jefrey Lijffijt
2019 J jnl
Discovering Interesting Cycles in Directed Graphs.
CoRR
Florian Adriaens, Çigdem Aslay, Tijl De Bie, Aristides Gionis, Jefrey Lijffijt
2019 — conf
EvalNE: A Framework for Evaluating Network Embeddings on Link Prediction.
RML@ICLR
Alexandru Mara, Jefrey Lijffijt, Tijl De Bie
2019 — conf
EvalNE: A Framework for Evaluating Network Embeddings on Link Prediction.
EDML@SDM
Alexandru Mara, Jefrey Lijffijt, Tijl De Bie
2019 J jnl
EvalNE: A Framework for Evaluating Network Embeddings on Link Prediction.
CoRR
Alexandru Mara, Jefrey Lijffijt, Tijl De Bie
2019 J jnl
ExplaiNE: An Approach for Explaining Network Embedding-based Link Predictions.
CoRR
Bo Kang, Jefrey Lijffijt, Tijl De Bie
2019 J jnl
Mining Subjectively Interesting Attributed Subgraphs.
CoRR
Anes Bendimerad, Ahmad Mel, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie
2019 J jnl
Opinion Dynamics with Backfire Effect and Biased Assimilation.
CoRR
Xi Chen, Panayiotis Tsaparas, Jefrey Lijffijt, Tijl De Bie
2019 J jnl
SIMIT: Subjectively Interesting Motifs in Time Series.
Entropy
Junning Deng, Jefrey Lijffijt, Bo Kang, Tijl De Bie
2019 J jnl
Subjectively interesting connecting trees and forests.
Data Min. Knowl. Discov.
Florian Adriaens, Jefrey Lijffijt, Tijl De Bie
2018 J jnl
Conditional Network Embeddings.
CoRR
Bo Kang, Jefrey Lijffijt, Tijl De Bie
2018 J jnl
From acquaintance to best friend forever: robust and fine-grained inference of social tie strengths.
CoRR
Florian Adriaens, Tijl De Bie, Aristides Gionis, Jefrey Lijffijt, Polina Rozenshtein
2018 A* conf
Interactive Visual Data Exploration with Subjective Feedback: An Information-Theoretic Approach.
ICDE
Kai Puolamäki, Emilia Oikarinen, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2018 A* conf
Quantifying and Minimizing Risk of Conflict in Social Networks.
KDD
Xi Chen, Jefrey Lijffijt, Tijl De Bie
2018 J jnl
SICA: subjectively interesting component analysis.
Data Min. Knowl. Discov.
Bo Kang, Jefrey Lijffijt, Raúl Santos-Rodríguez, Tijl De Bie
2018 A* conf
Subjectively Interesting Subgroup Discovery on Real-Valued Targets.
ICDE
Jefrey Lijffijt, Bo Kang, Wouter Duivesteijn, Kai Puolamäki, Emilia Oikarinen, Tijl De Bie
2017 B conf
Hierarchical Novelty Detection.
IDA
Paolo Simeone, Raúl Santos-Rodríguez, Matt McVicar, Jefrey Lijffijt, Tijl De Bie
2017 J jnl
Interactive Visual Data Exploration with Subjective Feedback: An Information-Theoretic Approach.
CoRR
Kai Puolamäki, Emilia Oikarinen, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2017 — conf
Subjectively Interesting Connecting Trees.
ECML/PKDD (2)
Florian Adriaens, Jefrey Lijffijt, Tijl De Bie
2017 J jnl
Subjectively Interesting Subgroup Discovery on Real-valued Targets.
CoRR
Jefrey Lijffijt, Bo Kang, Wouter Duivesteijn, Kai Puolamäki, Emilia Oikarinen, Tijl De Bie
2016 — conf
A Tool for Subjective and Interactive Visual Data Exploration.
ECML/PKDD (3)
Bo Kang, Kai Puolamäki, Jefrey Lijffijt, Tijl De Bie
2016 — conf
Detecting trends in twitter time series.
MLSP
Tijl De Bie, Jefrey Lijffijt, Cédric Mesnage, Raúl Santos-Rodriguez
2016 A* conf
Direct Mining of Subjectively Interesting Relational Patterns.
ICDM
Tias Guns, Achille Aknin, Jefrey Lijffijt, Tijl De Bie
2016 B conf
Informative data projections: a framework and two examples.
ESANN
Tijl De Bie, Jefrey Lijffijt, Raúl Santos-Rodríguez, Bo Kang
2016 — conf
Interactive Visual Data Exploration with Subjective Feedback.
ECML/PKDD (2)
Kai Puolamäki, Bo Kang, Jefrey Lijffijt, Tijl De Bie
2016 J jnl
P-N-RMiner: a generic framework for mining interesting structured relational patterns.
Int. J. Data Sci. Anal.
Jefrey Lijffijt, Eirini Spyropoulou, Bo Kang, Tijl De Bie
2016 J jnl
Significance testing of word frequencies in corpora.
Digit. Scholarsh. Humanit.
Jefrey Lijffijt, Terttu Nevalainen, Tanja Säily, Panagiotis Papapetrou, Kai Puolamäki, Heikki Mannila
2016 J jnl
SuMoTED: An intuitive edit distance between rooted unordered uniquely-labelled trees.
Pattern Recognit. Lett.
Matt McVicar, Benjamin Sach, Cédric Mesnage, Jefrey Lijffijt, Eirini Spyropoulou, Tijl De Bie
2016 A* conf
Subjectively Interesting Component Analysis: Data Projections that Contrast with Prior Expectations.
KDD
Bo Kang, Jefrey Lijffijt, Raúl Santos-Rodriguez, Tijl De Bie
2015 A conf
Covering the Egonet: A Crowdsourcing Approach to Social Circle Discovery on Twitter.
ICWSM
Karmen Lata Dykstra, Jefrey Lijffijt, Aristides Gionis
2015 J jnl
Informative Data Projections: A Framework and Two Examples.
CoRR
Tijl De Bie, Jefrey Lijffijt, Raúl Santos-Rodriguez, Bo Kang
2015 — conf
Interactively Exploring Supply and Demand in the UK Independent Music Scene.
ECML/PKDD (3)
Matt McVicar, Cédric Mesnage, Jefrey Lijffijt, Tijl De Bie
2015 B conf
P-N-RMiner: A generic framework for mining interesting structured relational patterns.
DSAA
Jefrey Lijffijt, Eirini Spyropoulou, Bo Kang, Tijl De Bie
2015 J jnl
Size matters: choosing the most informative set of window lengths for mining patterns in event sequences.
Data Min. Knowl. Discov.
Jefrey Lijffijt, Panagiotis Papapetrou, Kai Puolamäki
2015 — conf
Supply and demand of independent UK music artists on the web.
WebSci
Matt McVicar, Cédric Mesnage, Jefrey Lijffijt, Eirini Spyropoulou, Tijl De Bie
2014 J jnl
A statistical significance testing approach to mining the most informative set of patterns.
Data Min. Knowl. Discov.
Jefrey Lijffijt, Panagiotis Papapetrou, Kai Puolamäki
2013 — conf
A Fast and Simple Method for Mining Subsequences with Surprising Event Counts.
ECML/PKDD (1)
Jefrey Lijffijt
2013 — —
Computational methods for comparison and exploration of event sequences.
Jefrey Lijffijt
2012 — conf
Size Matters: Finding the Most Informative Set of Window Lengths.
ECML/PKDD (2)
Jefrey Lijffijt, Panagiotis Papapetrou, Kai Puolamäki
2011 — conf
Analyzing Word Frequencies in Large Text Corpora Using Inter-arrival Times and Bootstrapping.
ECML/PKDD (2)
Jefrey Lijffijt, Panagiotis Papapetrou, Kai Puolamäki, Heikki Mannila
2010 — conf
Benchmarking dynamic time warping for music retrieval.
PETRA
Jefrey Lijffijt, Panagiotis Papapetrou, Jaakko Hollmén, Vassilis Athitsos
2010 — conf
Tracking your steps on the track: body sensor recordings of a controlled walking experiment.
PETRA
Jefrey Lijffijt, Panagiotis Papapetrou, Jaakko Hollmén
2010 — conf
Visually Controllable Data Mining Methods.
ICDM Workshops
Kai Puolamäki, Panagiotis Papapetrou, Jefrey Lijffijt