Similarity and Compatibility in Fuzzy Set Theory : Assessment and Applications. Cet article n’est pas disponible.
Langue : anglais
Edité par Physica, 2010
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- Titre
- Similarity and Compatibility in Fuzzy Set Theory : Assessment and Applications
- Auteur
- Cross, Valerie V.; Sudkamp, Thomas A.
- Éditeur
- Physica
- Année de publication
- 2010
- État de l'article
- As New
- Reliure
- Couverture souple
- Langue
- anglais
- ISBN à 10 chiffres
- 3790825077
- ISBN à 13 chiffres
- 9783790825077
Assessing the degree to which two objects, an object and a query, or two concepts are similar or compatible is a fundamental component of human reasoning and consequently is critical in the development of automated diagnosis, classification, information retrieval and decision systems. The assessment of similarity has played an important role in such diverse disciplines such as taxonomy, psychology, and the social sciences. Each discipline has proposed methods for quantifying similarity judgments suitable for its particular applications. This book presents a unified approach to quantifying similarity and compatibility within the framework of fuzzy set theory and examines the primary importance of these concepts in approximate reasoning. Examples of the application of similarity measures in various areas including expert systems, information retrieval, and intelligent database systems are provided.
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Présentation de l'éditeur
Assessing the degree to which two objects, an object and a query, or two concepts are similar or compatible is a fundamental component of human reasoning and consequently is critical in the development of automated diagnosis, classification, information retrieval and decision systems. The assessment of similarity has played an important role in such diverse disciplines such as taxonomy, psychology, and the social sciences. Each discipline has proposed methods for quantifying similarity judgments suitable for its particular applications. This book presents a unified approach to quantifying similarity and compatibility within the framework of fuzzy set theory and examines the primary importance of these concepts in approximate reasoning. Examples of the application of similarity measures in various areas including expert systems, information retrieval, and intelligent database systems are provided.
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