Abstract
In this short paper we sketch a brief introduction to our Krimp algorithm. Moreover, we briefly discuss some of the large body of follow up research. Pointers to the relevant papers are provided in the bibliography.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Agrawal, R., Mannila, H., Srikant, R., Toivonen, H., Inkeri Verkamo, A.: Fast discovery of association rules. In: Fayyad, U.M., Piatetsky-Shapiro, G., Smyth, P., Uthurusamy, R. (eds.) Advances in Knowledge Discovery and Data Mining, pp. 307–328. AAAI/MIT Press (1996)
Bathoorn, R., Siebes, A.: Constructing (almost) phylogenetic trees from developmental sequences data. In: Boulicaut, J.-F., Esposito, F., Giannotti, F., Pedreschi, D. (eds.) PKDD 2004. LNCS (LNAI), vol. 3202, pp. 500–502. Springer, Heidelberg (2004)
Bertens, R., Siebes, A.: Characterising seismic data. In: ICDM 2014 Proceedings. IEEE (2014)
Boulicaut, J.-F., Bykowski, A., Rigotti, C.: Free-sets: a condensed representation of boolean data for the approximation of frequency queries. Data Mining and Knowledge Discovery 7(1), 5–22 (2003)
Calders, T., Goethals, B.: Non-derivable itemset mining. Data Mining and Knowledge Discovery 14(1), 171–206 (2007)
Cover, T.M., Thomas, J.A.: Elements of Information Theory. Wiley- Interscience, New York (2006)
Grünwald, P.: The Minimum Description Length Principle. MIT Press (2007)
Boulicaut, J.-F., De Raedt, L., Mannila, H. (eds.): Constraint-Based Mining and Inductive Databases. LNCS (LNAI), vol. 3848. Springer, Heidelberg (2005)
Koopman, A., Siebes, A.: Characteristic relational patterns. In: KDD 2009 Proceedings, pp. 437–446 (2009)
Mannila, H., Toivonen, H., Inkeri Verkamo, A.: Levelwise search and borders of theories in knowledge discovery. Data Mining and Knowledge Discovery 1(3), 241–258 (1997)
Pasquier, N., Bastide, Y., Taouil, R., Lakhal, L.: Discovering frequent closed itemsets for association rules. In: Beeri, C., Bruneman, P. (eds.) ICDT 1999. LNCS, vol. 1540, pp. 398–416. Springer, Heidelberg (1999)
Siebes, A., Kersten, R.: A structure function for transaction data. In: SDM 2011 Proceedings, pp. 558–569. SIAM (2011)
Siebes, A., Kersten, R.: Smoothing categorical data. In: Flach, P.A., De Bie, T., Cristianini, N. (eds.) ECML PKDD 2012, Part I. LNCS, vol. 7523, pp. 42–57. Springer, Heidelberg (2012)
Siebes, A., Vreeken, J., van Leeuwen, M.: Item sets that compress. In: SDM 2006 Proceedings, pp. 393–404. SIAM (2006)
Smets, K., Vreeken, J.: The odd one out: Identifying and characterising anomalies. In: SDM 2011Proceedings, pp. 804–815 (2011)
Smets, K., Vreeken, J.: Slim: Directly mining descriptive patterns. In: SDM 2012 Proceedings, pp. 236–247 (2012)
van Leeuwen, M., Siebes, A.: Streamkrimp: Detecting change in data streams. In: Daelemans, W., Goethals, B., Morik, K. (eds.) ECML PKDD 2008, Part I. LNCS (LNAI), vol. 5211, pp. 672–687. Springer, Heidelberg (2008)
van Leeuwen, M., Vreeken, J., Siebes, A.: Compression picks item sets that matter. In: Fürnkranz, J., Scheffer, T., Spiliopoulou, M. (eds.) PKDD 2006. LNCS (LNAI), vol. 4213, pp. 585–592. Springer, Heidelberg (2006)
van Leeuwen, M., Vreeken, J., Siebes, A.: Identifying the components. Data Mining and Knowledge Discovery 19(2), 173–292 (2009)
Vreeken, J., Siebes, A.: Filling in the blanks: Krimp minimisation for missing data. In: ICDM 2008 Proceedings, pp. 1067–1072. IEEE (2008)
Vreeken, J., van Leeuwen, M., Siebes, A.: Preserving privacy through data generation. In: ICDM 2007 Proceedings, pp. 685–690. IEEE (2007)
Vreeken, J., van Leeuwen, M., Siebes, A.: Krimp: Mining itemsets that compress. Data Mining and Knowledge Discovery 23(1), 169–214 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Siebes, A. (2014). MDL in Pattern Mining A Brief Introduction to Krimp . In: Glodeanu, C.V., Kaytoue, M., Sacarea, C. (eds) Formal Concept Analysis. ICFCA 2014. Lecture Notes in Computer Science(), vol 8478. Springer, Cham. https://doi.org/10.1007/978-3-319-07248-7_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-07248-7_3
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07247-0
Online ISBN: 978-3-319-07248-7
eBook Packages: Computer ScienceComputer Science (R0)