Publications per year


In Press

Boley, M, Goldsmith, BR, Ghiringhelli, LM & Vreeken, J Identifying Consistent Statements about Numerical Data with Dispersion-Corrected Subgroup Discovery. Data Mining and Knowledge Discovery, Springer (IF 3.160) (ECML PKDD'17 Journal Track)
Fischer, AK, Vreeken, J & Klakow, D Beyond Pairwise Similarity: Quantifying and Characterizing Linguistic Similarity between Groups of Languages by MDL. Computación y Sistemas (Special Issue for the 18th International Conference on Intelligent Text Processing and Computational Linguistics, CICLing'17)

2017

Budhathoki, K & Vreeken, J Causal Inference on Discrete Data by Stochastic Complexity. In: Proceedings of the IEEE International Conference on Data Mining (ICDM'17), IEEE, 2017. (19.9% acceptance rate)website
Kalofolias, J, Boley, M & Vreeken, J Efficiently Discovering Locally Exceptional yet Globally Representative Subgroups. In: Proceedings of the IEEE International Conference on Data Mining (ICDM'17), IEEE, 2017. (full paper, 9.3% acceptance rate; overall 19.9%)
Marx, A & Vreeken, J Telling Cause from Effect by MDL-based Local and Global Regression. In: Proceedings of the IEEE International Conference on Data Mining (ICDM'17), IEEE, 2017. (full paper, 9.3% acceptance rate; overall 19.9%)
Mandros, P, Boley, M & Vreeken, J Discovering Reliable Approximate Functional Dependencies. In: Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), ACM, 2017. (oral presentation, 8.6% acceptance rate; overall 17.5%)website
Bertens, R, Vreeken, J & Siebes, A Efficiently Discovering Unexpected Pattern-Co-Occurrences. In: Proceedings of the SIAM International Conference on Data Mining (SDM), SIAM, 2017. (overall 26% acceptance rate)
Bhattacharyya, A & Vreeken, J Efficiently Summarising Event Sequences with Rich Interleaving Patterns. In: Proceedings of the SIAM Conference on Data Mining (SDM), SIAM, 2017. (selected in the top 10 papers of SDM'17; overall 26% acceptance rate)website
Budhathoki, K & Vreeken, J Correlation by Compression. In: Proceedings of the SIAM Conference on Data Mining (SDM), SIAM, 2017. (overall 26% acceptance rate)website
Pienta, R, Kahng, M, Lin, Z, Vreeken, J, Talukdar, P, Abello, J, Parameswaran, G & Chau, DH Adaptive Local Exploration of Large Graphs. In: Proceedings of the SIAM International Conference on Data Mining (SDM), SIAM, 2017. (overall 26% acceptance rate)website
Goldsmith, B, Boley, M, Vreeken, J, Scheffler, M & Ghiringhelli, L Uncovering Structure-Property Relationships of Materials by Subgroup Discovery. New Journal of Physics vol.19, IOP Publishing Ltd and Deutsche Physikalische Gesellschaft, 2017. (IF 3.57)
Grosse, K & Vreeken, J Summarising Event Sequences using Serial Episodes and an Ontology. In: Proceedings of the 4th Workshop on Interactions between Data Mining and Natural Language Processing (DMNLP'17), pp 33-48, CEUR Workshop Proceedings, 2017.
Hinrichs, F & Vreeken, J Characterising the Difference and the Norm between Sequences Databases. In: Proceedings of the 4th Workshop on Interactions between Data Mining and Natural Language Processing (DMNLP'17), pp 49-64, CEUR Workshop Proceedings, 2017.
Hinrichs, F Finding Difference and Norm between Sequence Databases. B.Sc. Thesis, Saarland University, 2017.

2016

Budhathoki, K & Vreeken, J Causal Inference by Compression. In: Proceedings of the IEEE International Conference on Data Mining (ICDM'16), IEEE, 2016. (regular paper, 8.5% acceptance rate; overall 19.6%)
Kalofolias, J, Galbrun, E & Miettinen, P From Sets of Good Redescriptions to Good Sets of Redescriptions. In: Proceedings of the IEEE International Conference on Data Mining (ICDM), IEEE, 2016. (regular paper, 8.5% acceptance rate; overall 19.6%)
Bertens, R, Vreeken, J & Siebes, A Keeping it Short and Simple: Summarising Complex Event Sequences with Multivariate Patterns. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'16), pp 735-744, ACM, 2016. (oral presentation, 8.9% acceptance rate; overall 18.1%)videowebsite
Rozenshtein, P, Gionis, A, Prakash, BA & Vreeken, J Reconstructing an Epidemic over Time. In: Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp 1835-1844, ACM, 2016. (overall 18.1% acceptance rate)website
Nguyen, H-V, Mandros, P & Vreeken, J Universal Dependency Analysis. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 792-800, SIAM, 2016. (overall 25% acceptance rate)implementation
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Nguyen, H-V & Vreeken, J Flexibly Mining Better Subgroups. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 585-593, SIAM, 2016. (overall 25% acceptance rate)implementation
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Nguyen, H-V & Vreeken, J Linear-time Detection of Non-Linear Changes in Massively High Dimensional Time Series. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 828-836, SIAM, 2016. (overall 25% acceptance rate)implementation
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Athukorala, K, Glowacka, D, Jacucci, G, Oulasvirta, A & Vreeken, J Is Exploratory Search Different? A Comparison of Information Search Behavior for Exploratory and Lookup Tasks. Journal of the Association for Information Science and Technology (JASIST) vol.67(11), pp 2635-2651, Wiley, 2016. (IF 2.26)
Chau, DH, Vreeken, J, van Leeuwen, M, Shahaf, D & Faloutsos, C (eds) Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA). , 2016.website
Frasconi, P, Landwehr, N, Manco, G & Vreeken, J (eds) Proceedings of the European Conference on Machine Learning and Principles and Practices of Knowledge Discovery in Data (ECMLPKDD). Springer, 2016. (Part I)website
Frasconi, P, Landwehr, N, Manco, G & Vreeken, J (eds) Proceedings of the European Conference on Machine Learning and Principles and Practices of Knowledge Discovery in Data (ECMLPKDD). Springer, 2016. (Part II)website
Baradaranshahroudi, A Fast Computation of Highest Correlated Segments in Multivariate Time-Series. M.Sc. Thesis, Saarland University, 2016.
Bhattacharyya, A Squish: Efficiently Summarising Sequences with Rich and Interleaving Patterns. M.Sc. Thesis, Saarland University, 2016.
Wójciak, BA Spaghetti: Finding Storylines in Large Collections of Documents. M.Sc. Thesis, Saarland University, 2016.
Halbe, M Skim: Alternative Candidate Selections for Slim through Sketching. B.Sc. Thesis, Saarland University, 2016.
Salyaeva, M Summarising and Recommending with Skipisodes. M.Sc. Thesis, Saarland University, 2016.
Grosse, K An Approach for Ontological Pattern-based Summarization. M.Sc. Thesis, Saarland University, 2016.
Gandhi, M Towards Summarising Large Transaction Databases. M.Sc. Thesis, Saarland University, 2016.

2015

Pienta, R, Lin, Z, Kahng, M, Vreeken, J, Talukdar, PP, Abello, J, Parameswaran, G & Chau, DH AdaptiveNav: Adaptive Discovery of Interesting and Surprising Nodes in Large Graphs. In: Proceedings of the IEEE Conference on Visualization (VIS), IEEE, 2015.video
Budhathoki, K & Vreeken, J The Difference and the Norm – Characterising Similarities and Differences between Databases. In: Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp 206-223, Springer, 2015.
website
Nguyen, H-V & Vreeken, J Non-Parametric Jensen-Shannon Divergence. In: Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp 173-189, Springer, 2015.website
Karaev, S, Miettinen, P & Vreeken, J Getting to Know the Unknown Unknowns: Destructive-Noise Resistant Boolean Matrix Factorization. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 325-333, SIAM, 2015.implementation
Sundareisan, S, Vreeken, J & Prakash, BA Hidden Hazards: Finding Missing Nodes in Large Graph Epidemics. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 415-423, SIAM, 2015.
Vreeken, J Causal Inference by Direction of Information. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 909-917, SIAM, 2015.website
Koutra, D, Kang, U, Vreeken, J & Faloutsos, C Summarizing and Understanding Large Graphs. Statistical Analysis and Data Mining vol.8(3), pp 183-202, Wiley, 2015.website
Zimek, A & Vreeken, J The Blind Men and the Elephant: About Meeting the Problem of Multiple Truths in Data from Clustering and Pattern Mining Perspectives. Machine Learning vol.98(1), pp 121-155, Springer, 2015. (IF 1.587)
Chau, DH, Vreeken, J, van Leeuwen, M, Shahaf, D & Faloutsos, C (eds) Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA). , 2015.website
Budhathoki, K Correlation by Compression. M.Sc. Thesis, Saarland University, 2015.
Mandros, P Information-Theoretic Supervised Feature Selection for Continuous Data. M.Sc. Thesis, Saarland University, 2015.

2014

Athukorala, K, Oulasvirta, A, Glowacka, D, Vreeken, J & Jaccuci, G Narrow or Broad? Estimating Subjective Specificity in Exploratory Search. In: Proceedings of ACM Conference on Information and Knowledge Management (CIKM), pp 819-828, ACM, 2014. (IR track full paper, overall 21% acceptance rate)
Kuzey, E, Vreeken, J & Weikum, G A Fresh Look on Knowledge Bases: Distilling Named Events from News. In: Proceedings of ACM Conference on Information and Knowledge Management (CIKM), pp 1689-1698, ACM, 2014. (KM track full paper, overall 21% acceptance rate)
Nguyen, H-V, Müller, E, Vreeken, J & Böhm, K Multivariate Maximal Correlation Analysis. In: Proceedings of the International Conference on Machine Learning (ICML), pp 775-783, JMLR: W&CP vol.32, 2014. (25.0% acceptance rate)implementation
Koutra, D, Kang, U, Vreeken, J & Faloutsos, C VoG: Summarizing and Understanding Large Graphs. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 91-99, SIAM, 2014. (fast track journal invitation, as one of the best of SDM'14; full paper with presentation, 15.4% acceptance rate)implementation
Miettinen, P & Vreeken, J mdl4bmf: Minimal Description Length for Boolean Matrix Factorization. Transactions on Knowledge Discovery from Data vol.8(4), pp 1-30, ACM, 2014. (IF 1.68)implementation
Wu, H, Vreeken, J, Tatti, N & Ramakrishnan, N Uncovering the Plot: Detecting Surprising Coalitions of Entities in Multi-Relational Schemas. Data Mining and Knowledge Discovery vol.28(5), pp 1398-1428, Springer, 2014. (IF 2.877) (ECML PKDD'14 Journal Track)
Nguyen, H-V, Müller, E, Vreeken, J & Böhm, K Unsupervised Interaction-Preserving Discretization of Multivariate Data. Data Mining and Knowledge Discovery vol.28(5), pp 1366-1397, Springer, 2014. (IF 2.877) (ECML PKDD'14 Journal Track)implementation
Prakash, BA, Vreeken, J & Faloutsos, C Efficiently Spotting the Starting Points of an Epidemic in a Large Graph. Knowledge and Information Systems vol.38(1), pp 35-59, Springer, 2014. (IF 2.225)implementation
Webb, G & Vreeken, J Efficient Discovery of the Most Interesting Associations. Transactions on Knowledge Discovery from Data vol.8(3), pp 1-31, ACM, 2014. (IF 1.68)implementation
Vreeken, J & Tatti, N Interesting Patterns. In: Aggarwal, CC & Han, J (eds) Frequent Pattern Mining, pp 105-134, pp 105-134, Springer, 2014.
van Leeuwen, M & Vreeken, J Mining and Using Sets of Patterns through Compression. In: Aggarwal, CC & Han, J (eds) Frequent Pattern Mining, pp 165-198, pp 165-198, Springer, 2014.
Zimek, A, Assent, I & Vreeken, J Frequent Pattern Mining Algorithms for Data Clustering. In: Aggarwal, CC & Han, J (eds) Frequent Pattern Mining, pp 403-424, pp 403-424, Springer, 2014.
Athukorala, K, Oulasvirta, A, Glowacka, D, Vreeken, J & Jacucci, G Supporting Exploratory Search Through User Modeling. In: Proceedings of the UMAP Joint Workshop on Personalized Information Access (PIA), pp 1-6, 2014.
Athukorala, K, Oulasvirta, A, Glowacka, D, Vreeken, J & Jacucci, G Interaction Model to Predict Subjective-Specificity of Search Results. In: Proceedings of the 22nd Conference on User Modeling, Adaptation and Personalization — Late-Breaking Results (UMAP), pp 1-6, 2014.
Gandhi, M & Vreeken, J Slimmer, outsmarting Slim. PhD Poster and Video at: the 13th International Symposium on Intelligent Data Analysis (IDA), Springer, 2014.
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Chau, DH, Vreeken, J, van Leeuwen, M & Faloutsos, C (eds) Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA). , 2014.website
Bier, S Causal Inference by Packing Data. B.Sc. Thesis, Saarland University, 2014.

2013

Akşehirli, E, Goethals, B, Müller, E & Vreeken, J Cartification: A Neighborhood Preserving Transformation for Mining High Dimensional Data. In: Proceedings of the IEEE International Conference on Data Mining (ICDM), pp 937-942, IEEE, 2013. (19.6% acceptance rate)website
Kontonasios, K-N, Vreeken, J & De Bie, T Maximum Entropy Models for Iteratively Identifying Subjectively Interesting Structure in Real-Valued Data. In: Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp 256-271, Springer, 2013.implementation
Ramon, J, Miettinen, P & Vreeken, J Detecting Bicliques in GF[q]. In: Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp 509-524, Springer, 2013.implementation
Akoglu, L, Vreeken, J, Tong, H, Chau, DH, Tatti, N & Faloutsos, C Mining Connection Pathways for Marked Nodes in Large Graphs. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 37-45, SIAM, 2013. (oral presentation, 14.4% acceptance rate; overal 25%)implementation
Nguyen, H-V, Müller, E, Vreeken, J, Keller, F & Böhm, K CMI: An Information-Theoretic Contrast Measure for Enhancing Subspace Cluster and Outlier Detection. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 198-206, SIAM, 2013. (oral presentation, 14.4% acceptance rate; overal 25%)website
Chau, DH, Vreeken, J, van Leeuwen, M & Faloutsos, C (eds) Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA). ACM, 2013.website