Publicaties
2020
Wetenschappelijke publicaties
Nanni, M., Andrienko, G. L., Barabási, A-L., Boldrini, C., Bonchi, F., Cattuto, C., Chiaromonte, F., Comandé, G., Conti, M., Coté, M., Dignum, F., Dignum, V., Domingo-Ferrer, J., Ferragina, P., Giannotti, F., Guidotti, R., Helbing, D., Kaski, K., Kertész, J., ... Vespignani, A. (2020). Give more data, awareness and control to individual citizens, and they will help COVID-19 containment. Transactions on Data Privacy, 13(1), 61-66. http://www.tdp.cat/issues16/abs.a389a20.php
Meppelink, J., Langen, J. V., Siebes, A., Spruit, M., & Visvizi, A. (2020). Beware Thy Bias: Scaling Mobile Phone Data to Measure Traffic Intensities. Sustainability, 12(9), [3631]. https://doi.org/10.3390/su12093631
Omta, W., van Heesbeen, R., Shen, Z., de Nobel, J., van der Velden, L., Medema, R., Siebes, A., Feelders, A., Brinkkemper, S., Klumperman, J., Spruit, M., Brinkhuis, M., & Egan, D. (2020). Combining Supervised and Unsupervised Machine Learning Methods for Phenotypic Functional Genomics Screening. SLAS Discovery, 25(6), 655–664. https://doi.org/10.1177/2472555220919345
2018
Wetenschappelijke publicaties
Duivesteijn, W., Siebes, A., & Ukkonen, A. (Eds.) (2018). Advances in Intelligent Data Analysis XVII - 17th International Symposium, IDA 2018, 's-Hertogenbosch, The Netherlands, October 24-26, 2018, Proceedings. (Lecture Notes in Computer Science). Springer. https://doi.org/10.1007/978-3-030-01768-2
Siebes, A. (2018). Data science as a language: challenges for computer science - a position paper. International Journal of Data Science and Analytics, 6(3), 177-187. https://doi.org/10.1007/s41060-018-0103-4
2017
Wetenschappelijke publicaties
Bertens, R., Vreeken, J., & Siebes, A. (2017). Efficiently Discovering Unexpected Pattern-Co-Occurrences. In N. V. Chawla, & W. Wang (Eds.), Proceedings of the 2017 SIAM International Conference on Data Mining, Houston, Texas, USA, April 27-29, 2017 (pp. 126-134). SIAM. https://doi.org/10.1137/1.9781611974973.15
Krak, T. E., Bock, J. D., & Siebes, A. (2017). Efficient Computation of Updated Lower Expectations for Imprecise Continuous-Time Hidden Markov Chains. In A. Antonucci, G. Corani, I. Couso, & S. Destercke (Eds.), Proceedings of the Tenth International Symposium on Imprecise Probability: Theories and Applications, Lugano, Switzerland, 10-14 July 2017 (Vol. 62, pp. 193-204). (Proceedings of Machine Learning Research). PMLR. http://proceedings.mlr.press/v62/krak17a.html
Krak, T. E., Bock, J. D., & Siebes, A. (2017). Imprecise continuous-time Markov chains. Int. J. Approx. Reason., 88, 452-528. https://doi.org/10.1016/j.ijar.2017.06.012
2016
Wetenschappelijke publicaties
Bertens, R., Vreeken, J., & Siebes, A. P. J. M. (2016). Keeping it Short and Simple: Summarising Complex Event Sequences with Multivariate Patterns. In KDD '16 Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 735-744). ACM. https://doi.org/10.1145/2939672.2939761
2014
Wetenschappelijke publicaties
Siebes, A. (2014). MDL in Pattern Mining A Brief Introduction to Krimp. In C. V. Glodeanu, M. Kaytoue, & C. Sacarea (Eds.), Formal Concept Analysis - 12th International Conference, ICFCA 2014, Cluj-Napoca, Romania, June 10-13, 2014. Proceedings (pp. 37-43). (Lecture Notes in Computer Science; Vol. 8478). Springer. https://doi.org/10.1007/978-3-319-07248-7_3
Bertens, R., & Siebes, A. (2014). Characterising Seismic Data. (Technical Report Series; No. UU-CS-2014-002). UU BETA ICS Departement Informatica.
https://dspace.library.uu.nl/bitstream/handle/1874/306322/2014_002.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/306322/2014_002.pdf?sequence=1
Bertens, R., & Siebes, A. P. J. M. (2014). Characterising Seismic Data. In Z. Obradovic, M. Zaki, P. Tan, A. Banerjee, C. Kamath, & S. Parthasarathy (Eds.), Proceedings of the 2014 SIAM International Conference on Data Mining (pp. 884-892). Society for Industrial and Applied Mathematics. https://doi.org/10.1137/1.9781611973440
2013
Overige resultaten
Tucker, A., Höppner, F., Siebes, A., & Swift, S. (Eds.) (2013). Advances in Intelligent Data Analysis XII - 12th International Symposium, IDA 2013, London, UK, October 17-19, 2013. Proceedings.
2012
Wetenschappelijke publicaties
Siebes, A., & Kersten, R. (2012). Smoothing Categorical Data. In P. A. Flach, T. D. Bie, & N. Cristianini (Eds.), Machine Learning and Knowledge Discovery in Databases - ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part I (Vol. 7523, pp. 42-57). (Lecture Notes in Computer Science). Springer.
Siebes, A. (2012). Queries for Data Analysis. In J. Hollmén, F. Klawonn, & A. Tucker (Eds.), Advances in Intelligent Data Analysis XI - 11th International Symposium, IDA 2012, Helsinki, Finland, October 25-27, 2012. Proceedings (Vol. 7619, pp. 7-22). (Lecture Notes in Computer Science). Springer.
Overige resultaten
Vreeken, J., Ling, C., Zaki, M. J., Siebes, A., Yu, J. X., Goethals, B., Webb, G. I., & Wu, X. (Eds.) (2012). 12th IEEE International Conference on Data Mining Workshops, ICDM Workshops, Brussels, Belgium, December 10, 2012, Proceedings.
Zaki, M. J., Siebes, A., Yu, J. X., Goethals, B., Webb, G. I., & Wu, X. (Eds.) (2012). 12th IEEE International Conference on Data Mining, ICDM 2012 Brussels, Belgium, December 10-13, 2012, Proceedings.
2011
Wetenschappelijke publicaties
Siebes, A., & Kersten, R. (2011). A Structure Function for Transaction Data. In B. Liu, H. Liu, C. Clifton, T. Washio, & C. Kamath (Eds.), Proceedings of the Eleventh SIAM International Conference on Data Mining, SDM 2011, April 28-30, 2011, Mesa, Arizona, USA (pp. 558-569). SIAM.
Vreeken, J., Leeuwen, M. V., & Siebes, A. (2011). Krimp: Mining Itemsets that Compress. Journal of Data Mining and Knowledge Discovery, 23(1), 169-214.
2010
Wetenschappelijke publicaties
Bathoorn, R., Welten, M. C. M., Richardson, M., Siebes, A., & Verbeek, F. J. (2010). Frequent Episode Mining to Support Pattern Analysis in Developmental Biology. In T. Dijkstra, E. Tsivtsivadze, E. Marchiori, & T. Heskes (Eds.), Pattern Recognition in Bioinformatics - 5th IAPR International Conference, PRIB 2010, Nijmegen, The Netherlands, September 22-24, 2010. Proceedings (Vol. 6282, pp. 253-263). (Lecture Notes in Computer Science). Springer.
Toma, T., Bosman, R-J., Siebes, A., Peek, N., & Abu-Hanna, A. (2010). Learning predictive models that use pattern discovery - A bootstrap evaluative approach applied in organ functioning sequences. Journal of Biomedical Informatics, 43(4), 578-586.
Puspitaningrum, D., & Siebes, A. P. J. M. (2010). Patterns on Queries. In Inductive Databases and Constraint-Based Data Mining Springer.
2009
Wetenschappelijke publicaties
Koopman, A. C. M., & Siebes, A. P. J. M. (2009). Characteristic relational patterns. In J. F. Elder, F. Fogelman-Soulié, P. A. Flach, & M. J. Zaki (Eds.), Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 437-446)
Koopman, A. C. M., & Siebes, A. P. J. M. (2009). Characteristic relational patterns. In KDD (pp. 437-446)
Siebes, A. P. J. M., & Puspitaningrum, D. (2009). Mining Databases to Mine Queries Faster. In W. L. Buntine, M. Grobelnik, D. Mladenic, & J. Shawe-Taylor (Eds.), Machine Learning and Knowledge Discovery in Databases (pp. 382-397). Springer.
van Leeuwen, M., Vreeken, J., & Siebes, A. P. J. M. (2009). Identifying the Components. Data Mining and Knowledge Discovery, 19(2), 176-193.
van Leeuwen, M., Bonchi, F., Sigurbjörnsson, B., & Siebes, A. P. J. M. (2009). Compressing Tags to Find Interesting Media Groups. In DW-L. Cheung, Y-L. Song, W. W. Chu, X. Hu, & J. J. Lin (Eds.), CIKM'09: Proceedings of the 18th ACM Conference on Information and Knowledge Management (pp. 1147-1156). ACM.
Adams, N. M., Robardet, C., Siebes, A. P. J. M., & Boulicaut, J. F. (2009). Advances in Intelligent Data Analysis VIII. In IDA Springer.
2008
Wetenschappelijke publicaties
Koopman, A. C. M., & Siebes, A. P. J. M. (2008). Discovering Relational Items Sets Efficiently. In SDM (pp. 108-119). SIAM. http://www.siam.org/proceedings/datamining/2008/dm08_10_Koopman.pdf
de Jong, E. D., Franke, L., & Siebes, A. P. J. M. (2008). On the Measurement of Genetic Interactions. In Proceedings of the 3rd international symposium on Computational Life Science
Vreeken, J., & Siebes, A. P. J. M. (2008). Krimp Minimisation for Missing Data Estimation. (UU-CS ed.) UU WINFI Informatica en Informatiekunde. http://www.cs.uu.nl/research/techreps/repo/CS-2008/2008-034.pdf
Vreeken, J., & Siebes, A. P. J. M. (2008). Filling in the Blanks - Krimp Minimisation for Missing Data. In F. Gianotti, D. Gunopoulos, F. Turini, C. Zaniolo, N. Ramakrishnan, & X. Wu (Eds.), Proceedings of the IEEE International Conference on Data Mining (pp. 1067-1072). IEEE.
2007
Wetenschappelijke publicaties
Vreeken, J., van Leeuwen, M., & Siebes, A. P. J. M. (2007). Characterising the Difference. (UU-CS ed.) UU WINFI Informatica en Informatiekunde. http://www.cs.uu.nl/research/techreps/UU-CS-2007-014.html
Vreeken, J., van Leeuwen, M., & Siebes, A. P. J. M. (2007). Privacy Preservation through Data Generation. (UU-CS ed.) UU WINFI Informatica en Informatiekunde. http://www.cs.uu.nl/research/techreps/UU-CS-2007-020.html
Vreeken, J., van Leeuwen, M., & Siebes, A. P. J. M. (2007). Characterising the Difference. In P. Berkin, R. Caruana, X. Wu, & S. Gaffney (Eds.), ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 765-774). ACM.
Vreeken, J., van Leeuwen, M., & Siebes, A. P. J. M. (2007). Preserving Privacy through Data Generation. In N. Ramakrishnan, O. Za�e, Y. Shi, C. W. Clifton, & X. Wu (Eds.), Proceedings of the IEEE International Conference on Data Mining (pp. 685-690). IEEE.
2006
Wetenschappelijke publicaties
Bathoorn, R. W., Koopman, A. C. M., & Siebes, A. P. J. M. (2006). Reducing the Frequent Pattern Set. In S. Tsumoto, C. W. Clifton, N. Zhong, X. Wu, J. Liu, B. W. Wah, & Y-M. Cheung (Eds.), ICDM '06: Proceedings of the 6th International Conference on Data Mining - Workshops (pp. 55-59). IEEE Computer Society.
van Leeuwen, M., Vreeken, J., & Siebes, A. P. J. M. (2006). Compression Picks the Significant Item Sets. UU WINFI Informatica en Informatiekunde.
https://dspace.library.uu.nl/bitstream/handle/1874/24646/leeuwen_06_compressionpicks.pdf?sequence=3
https://dspace.library.uu.nl/bitstream/handle/1874/24646/leeuwen_06_compressionpicks.pdf?sequence=3
Bathoorn, R. W., Koopman, A. C. M., & Siebes, A. P. J. M. (2006). Frequent Patterns that Compress. UU WINFI Informatica en Informatiekunde.
https://dspace.library.uu.nl/bitstream/handle/1874/24615/bathoorn_06_frequentpatterns.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/24615/bathoorn_06_frequentpatterns.pdf?sequence=1
Malik, R., Franke, L. H., & Siebes, A. P. J. M. (2006). Combination of text-mining algorithms increases the performance. Bioinformatics, 22(17), 2151-2157.
Overige resultaten
de Jong, E. D., & Siebes, A. P. J. M. (2006). Evaluation of a Gene Network Extraction Method on Synthetic Data.
2005
Wetenschappelijke publicaties
Malik, R., & Siebes, A. P. J. M. (2005). CONAN: An Integrative System for Biomedical Literature Mining. In C. Bento, A. Cardoso, & G. Dias (Eds.), Progress in Artificial Intelligence, 12th Portuguese Conference on Artificial Intelligence, EPIA 2005 (pp. 248-259). Springer.
https://dspace.library.uu.nl/bitstream/handle/1874/10631/Malik_document.pdf?sequence=2
https://dspace.library.uu.nl/bitstream/handle/1874/10631/Malik_document.pdf?sequence=2
Goethals, B., & Siebes, A. P. J. M. (2005). KDID 2004, Knowledge Discovery in Inductive Databases, Proceedings of the Third International Workshop on Knowledge Discovery in Inductive Databases, Revised Selected and Invited Papers. (Lecture Notes in Computer Science ed.) Springer.
Morik, K., Boulicaut, J. F., & Siebes, A. P. J. M. (2005). Local Pattern Detection, International Seminar, Revised Selected Papers. (Lecture Notes in Computer Science ed.) Springer.
Siebes, A. P. J. M., Subianto, M., & Feelders, A. J. (2005). Instability of Classifiers on Categorical Data. In J. Han, B. W. Wah, V. Raghavan, X. Wu, & R. Rastogi (Eds.), Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005) (pp. 769-772). IEEE Computer Society.
Famili, A. F., Kok, J. N., Peña, A. S., Siebes, A. P. J. M., & Feelders, A. J. (2005). Advances in Intelligent Data Analysis VI, 6th International Symposium on Intelligent Data Analysis, IDA 2005. (Lecture Notes in Computer Science ed.) Springer.
2004
Wetenschappelijke publicaties
Egmont-Petersen, M., de Jonge, W., & Siebes, A. P. J. M. (2004). Discovery of regulatory connections in microarray data. In J-F. Boulicaut, F. Esposito, F. Giannotti, & D. Pedreschi (Eds.), Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) 2004 (pp. 149-160)
Siebes, A. P. J. M. (2004). Data submission of 3D image sets to a bio-molecular database using active shape models and a reference model for projection. In F. J. Verbeek, D. D. Rodrigues, H. P. Spaink, & A. Siebes (Eds.), Proceedings Electronic Imaging, Internet Imaging V (pp. 13-23)
Bathoorn, R. W., & Siebes, A. P. J. M. (2004). Constructing (Almost) Phylogenetic Trees from Developmental Sequences Data. In J-F. Boulicaut, F. Esposito, F. Giannotti, & D. Pedreschi (Eds.), Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) (pp. 500-502). Springer.
2002
Wetenschappelijke publicaties
Siebes, A. P. J. M. (2002). Data Surveyor. In W. Kloesgen, & J. M. Zytkow (Eds.), Handbook of data Mining nd Knowledge Discovery (pp. 572-575). Oxford University Press.
Struzik, Z. R., & Siebes, A. P. J. M. (2002). Wavelet transform based multifractal formalism in outlier detection and localisation for financial time-series. Physica. A, theoretical and statistical physics, 309, 388-402.
Siebes, A. P. J. M., & Struzik, Z. R. (2002). Complex data: mining using patterns. In D. J. Hand, N. Adams, & R. J. Bolton (Eds.), Pattern Detection and Discovery, proceedings of the ESF exploratory workshop (pp. 24-35). Springer.
Knobbe, A. J., Siebes, A. P. J. M., & Marseille, B. (2002). Involving aggregate functions in multi-relational search. In T. Elomaa, H. Mannila, & H. Toivonen (Eds.), Principles of Data Mining and Knowledge Discovery, proceedings of PKDD2002 (pp. 287-298). Springer.
van Someren, M., Siebes, A. P. J. M., Verdenius, F., & Meij, J. (2002). Methodology. In J. Meij (Ed.), Dealing with the data flood (pp. 540-551). STT/Beweton.
Siebes, A. P. J. M. (2002). From Discovered Knowledge to Decision Making. In W. Kloesgen, & J. M. Zytkow (Eds.), Handbook of Data Mining and Knowledge Discovery (pp. 524-528). Oxford University Press.
Siebes, A. P. J. M. (2002). Association Rules. In J. Meij (Ed.), Dealing with the data flood (pp. 646-649). STT/Beweton.
Siebes, A. P. J. M. (2002). Naive Bayes. In J. Meij (Ed.), Dealing with the data flood (pp. 666-690). STT/Beweton.
2001
Wetenschappelijke publicaties
Knobbe, A. J., de Haas, M., & Siebes, A. P. J. M. (2001). Propositionalisation and Aggregates. In L. de Raedt, & A. Siebes (Eds.), Principles of Data Mining and Knowledge Discovery (pp. 277-288). Springer.
de Raedt, L., & Siebes, A. P. J. M. (2001). Principles of Data Mining and Knowledge Discovery. Springer.
Castelo Valdueza, R., Feelders, A. J., & Siebes, A. P. J. M. (2001). Mambo: Discovering Association Rules Based on Conditional Independencies. In F. Hoffmann, D. J. Hand, N. Adams, D. Fisher, & G. Guimaraes (Eds.), Advances in Intelligent Data Analysis (pp. 289-298). Springer.
2000
Wetenschappelijke publicaties
Castelo Valdueza, R., & Siebes, A. P. J. M. (2000). A characterization of moral transitive directed acyclic graph Markov models as trees and its properties. (UU-CS ed.) Utrecht University: Information and Computing Sciences. http://www.cs.uu.nl/research/techreps/UU-CS-2000-44.html