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ORCIDKleanthis-Nikolaos Kontonasios
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2010 – 2019
- 2015
[j3]Kleanthis-Nikolaos Kontonasios, Tijl De Bie:
Subjectively interesting alternative clusterings. Mach. Learn. 98(1-2): 31-56 (2015)- 2013
- [b1]Kleanthis-Nikolaos Kontonasios:
Maximum entropy modelling for quantifying unexpectedness of data mining results. University of Bristol, UK, 2013 - [c4]Kleanthis-Nikolaos Kontonasios, Jilles Vreeken
, Tijl De Bie:
Maximum Entropy Models for Iteratively Identifying Subjectively Interesting Structure in Real-Valued Data. ECML/PKDD (2) 2013: 256-271 - 2012
- [j2]Kleanthis-Nikolaos Kontonasios, Eirini Spyropoulou, Tijl De Bie:
Knowledge discovery interestingness measures based on unexpectedness. WIREs Data Mining Knowl. Discov. 2(5): 386-399 (2012) - [c3]Kleanthis-Nikolaos Kontonasios, Tijl De Bie:
Formalizing Complex Prior Information to Quantify Subjective Interestingness of Frequent Pattern Sets. IDA 2012: 161-171 - 2011
- [c2]Kleanthis-Nikolaos Kontonasios, Jilles Vreeken, Tijl De Bie:
Maximum Entropy Modelling for Assessing Results on Real-Valued Data. ICDM 2011: 350-359 - 2010
- [j1]Tijl De Bie, Kleanthis-Nikolaos Kontonasios, Eirini Spyropoulou:
A framework for mining interesting pattern sets. SIGKDD Explor. 12(2): 92-100 (2010) - [c1]Kleanthis-Nikolaos Kontonasios, Tijl De Bie:
An Information-Theoretic Approach to Finding Informative Noisy Tiles in Binary Databases. SDM 2010: 153-164
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