Upper semi-lattice of binary strings with the relation "x is simple conditional to y"
Theoretical Computer Science
Logical operations and Kolmogorov complexity
Theoretical Computer Science
Independent minimum length programs to translate between given strings
Theoretical Computer Science
Information distance and conditional complexities
Theoretical Computer Science
Logical Operations and Kolmogorov Complexity II
CCC '01 Proceedings of the 16th Annual Conference on Computational Complexity
Systems of Strings with High Mutual Complexity
Problems of Information Transmission
Algorithmic Clustering of Music Based on String Compression
Computer Music Journal
Compression-based data mining of sequential data
Data Mining and Knowledge Discovery
An Introduction to Kolmogorov Complexity and Its Applications
An Introduction to Kolmogorov Complexity and Its Applications
Notes on Sum-Tests and Independence Tests
Theory of Computing Systems
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Studying software evolution using artefacts' shared information content
Science of Computer Programming
Evaluation of analogical proportions through Kolmogorov complexity
Knowledge-Based Systems
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Normalized information distance (NID) uses the theoretical notion of Kolmogorov complexity, which for practical purposes is approximated by the length of the compressed version of the file involved, using a real-world compression program. This practical application is called 'normalized compression distance' and it is trivially computable. It is a parameter-free similarity measure based on compression, and is used in pattern recognition, data mining, phylogeny, clustering, and classification. The complexity properties of its theoretical precursor, the NID, have been open. We show that the NID is neither upper semicomputable nor lower semicomputable.