Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Some inequalities for information divergence and related measures of discrimination
IEEE Transactions on Information Theory
Using identity credential usage logs to detect anomalous service accesses
Proceedings of the 5th ACM workshop on Digital identity management
Content-based scene detection and analysis method for automatic classification of TV sports news
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
Evaluation of histogram-based similarity functions for different color spaces
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
How to select microscopy image similarity metrics?
Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Multidimensional scaling analysis of fractional systems
Computers & Mathematics with Applications
A hierarchical semantic-based distance for nominal histogram comparison
Data & Knowledge Engineering
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Distance or similarity measures are of fundamental importance to pattern classification, clustering, and information retrieval problems. Various distance/similarity measures that are applicable to compare two nominal type histograms are reviewed and categorized in both syntactic and semantic relationships. A correlation coefficient and a hierarchical clustering technique are adopted to reveal similarities among numerous distance/similarity measures.