1.

Record Nr.

UNINA9910842293703321

Autore

Szkatula Grazyna

Titolo

Bidirectional Comparison of Nominal Sets : Asymmetry of Proximity / / by Grażyna Szkatuła, Maciej Krawczak

Pubbl/distr/stampa

Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024

ISBN

3-031-53096-9

Edizione

[1st ed. 2024.]

Descrizione fisica

1 online resource (218 pages)

Collana

Studies in Computational Intelligence, , 1860-9503 ; ; 1140

Disciplina

514.323

Soggetti

Engineering - Data processing

Computational intelligence

Engineering mathematics

Data Engineering

Computational Intelligence

Mathematical and Computational Engineering Applications

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Introduction and main assumptions -- Issues of asymmetry of data proximity -- Matching between ordinary sets -- Matching between sets with binary coding -- Matching between multisets -- Matching between fuzzy sets -- Matching between intuitionistic fuzzy sets -- Summary and perspectives.

Sommario/riassunto

The authors propose a novel measure of proximity between two sets of nominal elements. This measure describes the changes in the first set after adding the second set or changes in the second set after adding the first set. It is crucial to note that this measure is not symmetric, it means that the perturbation of the first set on the second set can be different than the perturbation of the opposition direction. The introduced set impact measure allows for the direct treatment of objects described by nominal-valued attributes. The ordinary sets, multisets, fuzzy sets, and the intuitionistic fuzzy sets are considered. The book is intended for data science professionals, philosophers as well as cognitive psychologists, who struggle with practical problems in which asymmetry of proximity of objects cannot be neglected. The use of the proposed measures of perturbation between compared objects



can be very important in data mining or in exploration of Internet resources.