| An information-theoretic approach to finding informative noisy tiles in binary databases KN Kontonasios, T De Bie Proceedings of the 2010 SIAM international conference on data mining, 153-164, 2010 | 71 | 2010 |
| Knowledge discovery interestingness measures based on unexpectedness KN Kontonasios, E Spyropoulou, T De Bie Wiley interdisciplinary reviews: data mining and knowledge discovery 2 (5 …, 2012 | 42 | 2012 |
| A framework for mining interesting pattern sets T De Bie, KN Kontonasios, E Spyropoulou ACM SIGKDD Explorations Newsletter 12 (2), 92-100, 2011 | 40 | 2011 |
| Maximum entropy modelling for assessing results on real-valued data KN Kontonasios, J Vreeken, T De Bie 2011 IEEE 11th International Conference on Data Mining, 350-359, 2011 | 22 | 2011 |
| Maximum entropy models for iteratively identifying subjectively interesting structure in real-valued data KN Kontonasios, J Vreeken, T De Bie Machine Learning and Knowledge Discovery in Databases: European Conference …, 2013 | 13 | 2013 |
| Formalizing complex prior information to quantify subjective interestingness of frequent pattern sets KN Kontonasios, T DeBie International Symposium on Intelligent Data Analysis, 161-171, 2012 | 12 | 2012 |
| Subjectively interesting alternative clusterings KN Kontonasios, T De Bie Machine Learning 98, 31-56, 2015 | 10 | 2015 |
| Formalizing complex prior information to quantify subjective interestingness of frequent pattern sets (supplementary document) KN Kontonasios, T DeBie Technical report, University of Bristol, 2011 | 1 | 2011 |
| Maximum entropy modelling for quantifying unexpectedness of data mining results KN Kontonasios University of Bristol, 2013 | | 2013 |
| Maximum Entropy Modeling for Real Valued Databases KN Kontonasios, V Jilles, BT De | | 2011 |
| Workshop Co-Chairs T De Bie, KN Kontonasios, E Spyropoulou | | |
Tijl De BieFull Professor, Ghent UniversityVerified email at ugent.be
