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Things to Know about a (dis)similarity Measure

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Knowledge-Based and Intelligent Information and Engineering Systems (KES 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6881))

Abstract

The notions of similarity and dissimilarity are widely used in many fields of Artificial Intelligence. They have many different and often partial definitions or properties, usually restricted to one field of application and thus incompatible with other uses. This paper contributes to the design and understanding of similarity and dissimilarity measures for Artificial Intelligence. A formal dual definition for each concept is proposed, joined with a set of fundamental properties. The behavior of the properties under several transformations is studied and revealed as an important matter to bear in mind. We also develop several practical examples that work out the proposed approach.

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© 2011 Springer-Verlag Berlin Heidelberg

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Belanche, L., Orozco, J. (2011). Things to Know about a (dis)similarity Measure. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2011. Lecture Notes in Computer Science(), vol 6881. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23851-2_11

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  • DOI: https://doi.org/10.1007/978-3-642-23851-2_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23850-5

  • Online ISBN: 978-3-642-23851-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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