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ORCIDJefrey Lijffijt
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- affiliation: Ghent University, Belgium
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2020 – today
- 2024
[j23]Yoosof Mashayekhi
, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Scalable Job Recommendation With Lower Congestion Using Optimal Transport. IEEE Access 12: 55491-55505 (2024)- [j22]Edith Heiter, Robin Vandaele, Tijl De Bie, Yvan Saeys, Jefrey Lijffijt:
Incorporating Topological Priors Into Low-Dimensional Visualizations Through Topological Regularization. IEEE Access 12: 129541-129573 (2024) - [j21]Yoosof Mashayekhi, Nan Li, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
A Challenge-based Survey of E-recruitment Recommendation Systems. ACM Comput. Surv. 56(10): 252 (2024) - [j20]Nan Li, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
FEIR: Quantifying and Reducing Envy and Inferiority for Fair Recommendation of Limited Resources. ACM Trans. Intell. Syst. Technol. 15(4): 80:1-80:24 (2024) - [j19]Yoosof Mashayekhi, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
GREASE: Graph Imbalance Reduction by Adding Sets of Edges. IEEE Trans. Knowl. Data Eng. 36(4): 1611-1623 (2024) - [c43]Edith Heiter, Liesbet Martens, Ruth Seurinck, Martin Guilliams, Tijl De Bie, Yvan Saeys, Jefrey Lijffijt:
Pattern or Artifact? Interactively Exploring Embedding Quality with TRACE. ECML/PKDD (8) 2024: 379-382 - [i30]Raphaël Romero, Maarten Buyl, Tijl De Bie, Jefrey Lijffijt:
Exploring the Performance of Continuous-Time Dynamic Link Prediction Algorithms. CoRR abs/2405.17182 (2024) - [i29]Raphaël Romero, Jefrey Lijffijt, Riccardo Rastelli, Marco Corneli, Tijl De Bie:
Gaussian Embedding of Temporal Networks. CoRR abs/2405.17253 (2024) - [i28]Edith Heiter, Liesbet Martens, Ruth Seurinck, Martin Guilliams, Tijl De Bie, Yvan Saeys, Jefrey Lijffijt:
Pattern or Artifact? Interactively Exploring Embedding Quality with TRACE. CoRR abs/2406.12953 (2024) - 2023
- [j18]Raphaël Romero, Jefrey Lijffijt, Riccardo Rastelli, Marco Corneli, Tijl De Bie:
Gaussian Embedding of Temporal Networks. IEEE Access 11: 117971-117983 (2023) - [c42]Nan Li, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
FEIR: Quantifying and Reducing Envy and Inferiority for Fair Recommendation of Limited Resources. HR@RecSys 2023 - [c41]Edith Heiter, Bo Kang, Ruth Seurinck, Jefrey Lijffijt:
Revised Conditional t-SNE: Looking Beyond the Nearest Neighbors. IDA 2023: 169-181 - [c40]Yoosof Mashayekhi, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
ReCon: Reducing Congestion in Job Recommendation using Optimal Transport. RecSys 2023: 696-701 - [e7]Toon Calders, Celine Vens, Jefrey Lijffijt, Bart Goethals:
Artificial Intelligence and Machine Learning - 34th Joint Benelux Conference, BNAIC/Benelearn 2022, Mechelen, Belgium, November 7-9, 2022, Revised Selected Papers. Communications in Computer and Information Science 1805, Springer 2023, ISBN 978-3-031-39143-9 [contents] - [i27]Edith Heiter, Robin Vandaele, Tijl De Bie, Yvan Saeys, Jefrey Lijffijt:
Topologically Regularized Data Embeddings. CoRR abs/2301.03338 (2023) - [i26]Edith Heiter, Bo Kang, Ruth Seurinck, Jefrey Lijffijt:
Revised Conditional t-SNE: Looking Beyond the Nearest Neighbors. CoRR abs/2302.03493 (2023) - [i25]Yoosof Mashayekhi, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
ReCon: Reducing Congestion in Job Recommendation using Optimal Transport. CoRR abs/2308.09516 (2023) - [i24]Nan Li, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
FEIR: Quantifying and Reducing Envy and Inferiority for Fair Recommendation of Limited Resources. CoRR abs/2311.04542 (2023) - [i23]Raphaël Romero, Tijl De Bie, Jefrey Lijffijt:
New Perspectives on the Evaluation of Link Prediction Algorithms for Dynamic Graphs. CoRR abs/2311.18486 (2023) - 2022
- [j17]Edith Heiter, Bo Kang, Tijl De Bie, Jefrey Lijffijt:
Evaluating Representation Learning and Graph Layout Methods for Visualization. IEEE Computer Graphics and Applications 42(3): 19-28 (2022) - [j16]Jefrey Lijffijt, Dimitra Gkorou, Pieter Van Hertum, Alexander Ypma, Mykola Pechenizkiy, Joaquin Vanschoren:
Introduction to the Special Section on AI in Manufacturing: Current Trends and Challenges. SIGKDD Explor. 24(2): 81-85 (2022) - [j15]Alexandru Mara, Jefrey Lijffijt, Tijl De Bie:
EvalNE: A framework for network embedding evaluation. SoftwareX 17: 100997 (2022) - [c39]Robin Vandaele, Bo Kang, Jefrey Lijffijt, Tijl De Bie, Yvan Saeys:
Topologically Regularized Data Embeddings. ICLR 2022 - [c38]Alexandru Cristian Mara, Jefrey Lijffijt, Stephan Günnemann, Tijl De Bie:
A Systematic Evaluation of Node Embedding Robustness. LoG 2022: 42 - [i22]Yoosof Mashayekhi, Nan Li, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
A challenge-based survey of e-recruitment recommendation systems. CoRR abs/2209.05112 (2022) - [i21]Alexandru Mara, Jefrey Lijffijt, Stephan Günnemann, Tijl De Bie:
A Systematic Evaluation of Node Embedding Robustness. CoRR abs/2209.08064 (2022) - 2021
- [j14]Junning Deng, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Mining explainable local and global subgraph patterns with surprising densities. Data Min. Knowl. Discov. 35(1): 321-371 (2021) - [j13]Bo Kang, Dario García-García, Jefrey Lijffijt, Raúl Santos-Rodríguez, Tijl De Bie:
Conditional t-SNE: more informative t-SNE embeddings. Mach. Learn. 110(10): 2905-2940 (2021) - [c37]Bo Kang, Dario García-García, Jefrey Lijffijt, Raúl Santos-Rodríguez, Tijl De Bie:
Conditional t-SNE: More informative t-SNE embeddings. DSAA 2021: 1-2 - [c36]Yoosof Mashayekhi, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Quantifying and Reducing Imbalance in Networks. HR@RecSys 2021 - [c35]Xi Chen, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Adversarial Robustness of Probabilistic Network Embedding for Link Prediction. PKDD/ECML Workshops (2) 2021: 22-38 - [c34]Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Explanations for Network Embedding-Based Link Predictions. PKDD/ECML Workshops (1) 2021: 473-488 - [e6]Mitra Baratchi, Lu Cao, Walter A. Kosters, Jefrey Lijffijt, Jan N. van Rijn, Frank W. Takes:
Artificial Intelligence and Machine Learning - 32nd Benelux Conference, BNAIC/Benelearn 2020, Leiden, The Netherlands, November 19-20, 2020, Revised Selected Papers. Communications in Computer and Information Science 1398, Springer 2021, ISBN 978-3-030-76639-9 [contents] - [e5]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 A. D. Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
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. Communications in Computer and Information Science 1524, Springer 2021, ISBN 978-3-030-93735-5 [contents] - [e4]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 A. D. Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
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. Communications in Computer and Information Science 1525, Springer 2021, ISBN 978-3-030-93732-4 [contents] - [e3]Frank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part I. Lecture Notes in Computer Science 12457, Springer 2021, ISBN 978-3-030-67657-5 [contents] - [e2]Frank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part II. Lecture Notes in Computer Science 12458, Springer 2021, ISBN 978-3-030-67660-5 [contents] - [e1]Frank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part III. Lecture Notes in Computer Science 12459, Springer 2021, ISBN 978-3-030-67663-6 [contents] - [i20]Xi Chen, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Adversarial Robustness of Probabilistic Network Embedding for Link Prediction. CoRR abs/2107.01936 (2021) - [i19]Robin Vandaele, Bo Kang, Jefrey Lijffijt, Tijl De Bie, Yvan Saeys:
Topologically Regularized Data Embeddings. CoRR abs/2110.09193 (2021) - [i18]Xander Vankwikelberge, Bo Kang, Edith Heiter, Jefrey Lijffijt:
ExClus: Explainable Clustering on Low-dimensional Data Representations. CoRR abs/2111.03168 (2021) - 2020
- [j12]Kai Puolamäki, Emilia Oikarinen, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Interactive visual data exploration with subjective feedback: an information-theoretic approach. Data Min. Knowl. Discov. 34(1): 21-49 (2020) - [j11]Anes Bendimerad, Ahmad Mel, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie:
SIAS-miner: mining subjectively interesting attributed subgraphs. Data Min. Knowl. Discov. 34(2): 355-393 (2020) - [j10]Florian Adriaens, Tijl De Bie, Aristides Gionis, Jefrey Lijffijt, Antonis Matakos, Polina Rozenshtein:
Relaxing the strong triadic closure problem for edge strength inference. Data Min. Knowl. Discov. 34(3): 611-651 (2020) - [j9]Bo Kang, Kai Puolamäki, Jefrey Lijffijt, Tijl De Bie:
A Constrained Randomization Approach to Interactive Visual Data Exploration with Subjective Feedback. IEEE Trans. Knowl. Data Eng. 32(9): 1666-1679 (2020) - [c33]Alexandru Mara, Yoosof Mashayekhi, Jefrey Lijffijt, Tijl De Bie:
CSNE: Conditional Signed Network Embedding. CIKM 2020: 1105-1114 - [c32]Florian Adriaens, Alexandru Mara, Jefrey Lijffijt, Tijl De Bie:
Block-Approximated Exponential Random Graphs. DSAA 2020: 70-80 - [c31]Alexandru Cristian Mara, Jefrey Lijffijt, Tijl De Bie:
Benchmarking Network Embedding Models for Link Prediction: Are We Making Progress? DSAA 2020: 138-147 - [c30]Ahmad Mel, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
FONDUE: Framework for Node Disambiguation Using Network Embeddings. DSAA 2020: 158-167 - [c29]Anes Bendimerad, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie:
Gibbs Sampling Subjectively Interesting Tiles. IDA 2020: 80-92 - [c28]Junning Deng, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Explainable Subgraphs with Surprising Densities: A Subgroup Discovery Approach. SDM 2020: 586-594 - [i17]Junning Deng, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Explainable Subgraphs with Surprising Densities: A Subgroup Discovery Approach. CoRR abs/2002.00793 (2020) - [i16]Xi Chen, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
ALPINE: Active Link Prediction using Network Embedding. CoRR abs/2002.01227 (2020) - [i15]Florian Adriaens, Alexandru Mara, Jefrey Lijffijt, Tijl De Bie:
Scalable Dyadic Independence Models with Local and Global Constraints. CoRR abs/2002.07076 (2020) - [i14]Ahmad Mel, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
FONDUE: A Framework for Node Disambiguation Using Network Embeddings. CoRR abs/2002.10127 (2020) - [i13]Alexandru Mara, Jefrey Lijffijt, Tijl De Bie:
Network Representation Learning for Link Prediction: Are we improving upon simple heuristics? CoRR abs/2002.11522 (2020) - [i12]Alexandru Mara, Yoosof Mashayekhi, Jefrey Lijffijt, Tijl De Bie:
CSNE: Conditional Signed Network Embedding. CoRR abs/2005.10701 (2020)
2010 – 2019
- 2019
- [j8]Florian Adriaens, Jefrey Lijffijt, Tijl De Bie:
Subjectively interesting connecting trees and forests. Data Min. Knowl. Discov. 33(4): 1088-1124 (2019) - [j7]Junning Deng, Jefrey Lijffijt, Bo Kang, Tijl De Bie:
SIMIT: Subjectively Interesting Motifs in Time Series. Entropy 21(6): 566 (2019) - [c27]Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Conditional Network Embeddings. BNAIC/BENELEARN 2019 - [c26]Florian Adriaens, Çigdem Aslay, Tijl De Bie, Aristides Gionis, Jefrey Lijffijt:
Discovering Interesting Cycles in Directed Graphs. CIKM 2019: 1191-1200 - [c25]Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Conditional Network Embeddings. ICLR (Poster) 2019 - [c24]Alexandru Mara, Jefrey Lijffijt, Tijl De Bie:
EvalNE: A Framework for Evaluating Network Embeddings on Link Prediction. RML@ICLR 2019 - [c23]Anes Bendimerad, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie:
Contrastive Antichains in Hierarchies. KDD 2019: 294-304 - [c22]Alexandru Mara, Jefrey Lijffijt, Tijl De Bie:
EvalNE: A Framework for Evaluating Network Embeddings on Link Prediction. EDML@SDM 2019: 5-13 - [i11]Alexandru Mara, Jefrey Lijffijt, Tijl De Bie:
EvalNE: A Framework for Evaluating Network Embeddings on Link Prediction. CoRR abs/1901.09691 (2019) - [i10]Xi Chen, Panayiotis Tsaparas, Jefrey Lijffijt, Tijl De Bie:
Opinion Dynamics with Backfire Effect and Biased Assimilation. CoRR abs/1903.11535 (2019) - [i9]Bo Kang, Jefrey Lijffijt, Tijl De Bie:
ExplaiNE: An Approach for Explaining Network Embedding-based Link Predictions. CoRR abs/1904.12694 (2019) - [i8]Anes Bendimerad, Ahmad Mel, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie:
Mining Subjectively Interesting Attributed Subgraphs. CoRR abs/1905.03040 (2019) - [i7]Bo Kang, Dario García-García, Jefrey Lijffijt, Raúl Santos-Rodríguez, Tijl De Bie:
Conditional t-SNE: Complementary t-SNE embeddings through factoring out prior information. CoRR abs/1905.10086 (2019) - [i6]Florian Adriaens, Çigdem Aslay, Tijl De Bie, Aristides Gionis, Jefrey Lijffijt:
Discovering Interesting Cycles in Directed Graphs. CoRR abs/1909.01060 (2019) - 2018
- [j6]Bo Kang, Jefrey Lijffijt, Raúl Santos-Rodríguez, Tijl De Bie:
SICA: subjectively interesting component analysis. Data Min. Knowl. Discov. 32(4): 949-987 (2018) - [c21]Kai Puolamäki, Emilia Oikarinen, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Interactive Visual Data Exploration with Subjective Feedback: An Information-Theoretic Approach. ICDE 2018: 1208-1211 - [c20]Jefrey Lijffijt, Bo Kang, Wouter Duivesteijn, Kai Puolamäki, Emilia Oikarinen, Tijl De Bie:
Subjectively Interesting Subgroup Discovery on Real-Valued Targets. ICDE 2018: 1352-1355 - [c19]Xi Chen, Jefrey Lijffijt, Tijl De Bie:
Quantifying and Minimizing Risk of Conflict in Social Networks. KDD 2018: 1197-1205 - [i5]Florian Adriaens, Tijl De Bie, Aristides Gionis, Jefrey Lijffijt, Polina Rozenshtein:
From acquaintance to best friend forever: robust and fine-grained inference of social tie strengths. CoRR abs/1802.03549 (2018) - [i4]Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Conditional Network Embeddings. CoRR abs/1805.07544 (2018) - 2017
- [c18]Paolo Simeone, Raúl Santos-Rodríguez, Matt McVicar, Jefrey Lijffijt, Tijl De Bie:
Hierarchical Novelty Detection. IDA 2017: 310-321 - [c17]Florian Adriaens, Jefrey Lijffijt, Tijl De Bie:
Subjectively Interesting Connecting Trees. ECML/PKDD (2) 2017: 53-69 - [i3]Jefrey Lijffijt, Bo Kang, Wouter Duivesteijn, Kai Puolamäki, Emilia Oikarinen, Tijl De Bie:
Subjectively Interesting Subgroup Discovery on Real-valued Targets. CoRR abs/1710.04521 (2017) - [i2]Kai Puolamäki, Emilia Oikarinen, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Interactive Visual Data Exploration with Subjective Feedback: An Information-Theoretic Approach. CoRR abs/1710.08167 (2017) - 2016
- [j5]Jefrey Lijffijt, Eirini Spyropoulou, Bo Kang, Tijl De Bie:
P-N-RMiner: a generic framework for mining interesting structured relational patterns. Int. J. Data Sci. Anal. 1(1): 61-76 (2016) - [j4]Jefrey Lijffijt, Terttu Nevalainen, Tanja Säily, Panagiotis Papapetrou, Kai Puolamäki, Heikki Mannila:
Significance testing of word frequencies in corpora. Digit. Scholarsh. Humanit. 31(2): 374-397 (2016) - [j3]Matt McVicar, Benjamin Sach, Cédric Mesnage, Jefrey Lijffijt, Eirini Spyropoulou, Tijl De Bie:
SuMoTED: An intuitive edit distance between rooted unordered uniquely-labelled trees. Pattern Recognit. Lett. 79: 52-59 (2016) - [c16]Tijl De Bie, Jefrey Lijffijt, Raúl Santos-Rodríguez, Bo Kang:
Informative data projections: a framework and two examples. ESANN 2016 - [c15]Tias Guns, Achille Aknin, Jefrey Lijffijt, Tijl De Bie:
Direct Mining of Subjectively Interesting Relational Patterns. ICDM 2016: 913-918 - [c14]Bo Kang, Jefrey Lijffijt, Raúl Santos-Rodriguez, Tijl De Bie:
Subjectively Interesting Component Analysis: Data Projections that Contrast with Prior Expectations. KDD 2016: 1615-1624 - [c13]Tijl De Bie, Jefrey Lijffijt, Cédric Mesnage, Raúl Santos-Rodriguez:
Detecting trends in twitter time series. MLSP 2016: 1-6 - [c12]Bo Kang, Kai Puolamäki, Jefrey Lijffijt, Tijl De Bie:
A Tool for Subjective and Interactive Visual Data Exploration. ECML/PKDD (3) 2016: 3-7 - [c11]Kai Puolamäki, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Interactive Visual Data Exploration with Subjective Feedback. ECML/PKDD (2) 2016: 214-229 - 2015
- [j2]Jefrey Lijffijt, Panagiotis Papapetrou, Kai Puolamäki:
Size matters: choosing the most informative set of window lengths for mining patterns in event sequences. Data Min. Knowl. Discov. 29(6): 1838-1864 (2015) - [c10]Jefrey Lijffijt, Eirini Spyropoulou, Bo Kang, Tijl De Bie:
P-N-RMiner: A generic framework for mining interesting structured relational patterns. DSAA 2015: 1-10 - [c9]Karmen Lata Dykstra, Jefrey Lijffijt, Aristides Gionis:
Covering the Egonet: A Crowdsourcing Approach to Social Circle Discovery on Twitter. ICWSM 2015: 606-609 - [c8]Matt McVicar, Cédric Mesnage, Jefrey Lijffijt, Tijl De Bie:
Interactively Exploring Supply and Demand in the UK Independent Music Scene. ECML/PKDD (3) 2015: 289-292 - [c7]Matt McVicar, Cédric Mesnage, Jefrey Lijffijt, Eirini Spyropoulou, Tijl De Bie:
Supply and demand of independent UK music artists on the web. WebSci 2015: 48:1-48:2 - [i1]Tijl De Bie, Jefrey Lijffijt, Raúl Santos-Rodriguez, Bo Kang:
Informative Data Projections: A Framework and Two Examples. CoRR abs/1511.08762 (2015) - 2014
- [j1]Jefrey Lijffijt, Panagiotis Papapetrou, Kai Puolamäki:
A statistical significance testing approach to mining the most informative set of patterns. Data Min. Knowl. Discov. 28(1): 238-263 (2014) - 2013
- [b1]Jefrey Lijffijt:
Computational methods for comparison and exploration of event sequences. Ghent University, Belgium, 2013 - [c6]Jefrey Lijffijt:
A Fast and Simple Method for Mining Subsequences with Surprising Event Counts. ECML/PKDD (1) 2013: 385-400 - 2012
- [c5]Jefrey Lijffijt, Panagiotis Papapetrou, Kai Puolamäki:
Size Matters: Finding the Most Informative Set of Window Lengths. ECML/PKDD (2) 2012: 451-466 - 2011
- [c4]Jefrey Lijffijt, Panagiotis Papapetrou, Kai Puolamäki, Heikki Mannila:
Analyzing Word Frequencies in Large Text Corpora Using Inter-arrival Times and Bootstrapping. ECML/PKDD (2) 2011: 341-357 - 2010
- [c3]Kai Puolamäki, Panagiotis Papapetrou, Jefrey Lijffijt:
Visually Controllable Data Mining Methods. ICDM Workshops 2010: 409-417 - [c2]Jefrey Lijffijt, Panagiotis Papapetrou, Jaakko Hollmén:
Tracking your steps on the track: body sensor recordings of a controlled walking experiment. PETRA 2010 - [c1]Jefrey Lijffijt, Panagiotis Papapetrou, Jaakko Hollmén, Vassilis Athitsos:
Benchmarking dynamic time warping for music retrieval. PETRA 2010
Coauthor Index
[j23] [j22] [j21] [j20] [j19] [c43] [i30] [i29] [i28] [j18] [c42] [c40] [i27] [i25] [i24] [i23] [j17] [j15] [c39] [c38] [i22] [i21] [j14] [j13] [c37] [c36] [c35] [c34] [i20] [i19] [j12] [j11] [j10] [j9] [c33] [c32] [c31] [c30] [c29] [c28] [i17] [i16] [i15] [i14] [i13] [i12] [j8] [j7] [c27] [c26] [c25] [c24] [c23] [c22] [i11] [i10] [i9] [i8] [i7] [i6] [j6] [c21] [c20] [c19] [i5] [i4] [c18] [c17] [i3] [i2] [j5] [j3] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [c8] [c7] [i1]
Alexandru Mara
aka: Alexandru Cristian Mara
aka: Alexandru Cristian Mara
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Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-13 18:00 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
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