Similarity and Dissimilarity Measures for Mixed Feature-Type Symbolic Data

Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 227)

Abstract

This paper presents some preliminary results for the similarity and dissimilarity measures based on the Cartesian System Model (CSM) that is a mathematical model to manipulate mixed feature-type symbolic data. We define the notion of concept size for the description of each object in the feature space. By extending the notion to the concept sizes of the Cartesian join and the Cartesian meet of the descriptions for objects, we can obtain various similarity and dissimilarity measures. We present especially asymmetric and symmetric similarity measures useful for pattern recognition problems.

Keywords

Cartesian system model Symbolic data Concept size Pattern recognition 

Notes

Acknowledgements

The authors thank anonymous referees for their helpful comments. This work was supported by JSPS KAKENHI (Grants–in–Aid for Scientific Research) Grant Number 25330268.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Tokyo Denki UniversityTokyoJapan
  2. 2.Tallinn University of TechnologyTallinnEstonia

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