Different types of search algorithms for rough sets

Nagy Dávid and Mihálydeák Tamás and Aszalós László: Different types of search algorithms for rough sets. In: Acta cybernetica, (24) 1. pp. 105-120. (2019)

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Based on the available information in many cases, it can happen that two objects cannot be distinguished. If a set of data is given and in this set two objects have the same attribute values, then these two objects are called indiscernible. This indiscernibility has an effect on the membership relation because in some cases it makes our judgment uncertain about a given object. The uncertainty appears because if something about an object needs to be stated, then all the objects that are indiscernible from the given object must be taken into consideration. The indiscernibility relation is an equivalence relation which represents the background knowledge embedded in an information system. In a Pawlakian system this relation is used in set approximation. Correlation clustering is a clustering technique which generates a partition. In the authors’ previous research, (see in [10, 11, 9]) the possible usage of correlation clustering in rough set theory was investigated. In this paper, the authors show how different types of search algorithms can affect the set approximation.

Item Type: Article
Journal or Publication Title: Acta cybernetica
Date: 2019
Volume: 24
Number: 1
ISSN: 0324-721X
Page Range: pp. 105-120
Language: English
Publisher: University of Szeged, Institute of Informatics
Place of Publication: Szeged
Event Title: Conference of PhD students in computer science (11.) (2018) (Szeged)
Related URLs: http://acta.bibl.u-szeged.hu/62212/
DOI: 10.14232/actacyb.24.1.2019.8
Uncontrolled Keywords: Számítástechnika, Algoritmus, Programozás
Additional Information: Bibliogr.: p. 119-120. ; összefoglalás angol nyelven
Subjects: 01. Natural sciences
01. Natural sciences > 01.02. Computer and information sciences
Date Deposited: 2019. Jul. 17. 13:39
Last Modified: 2022. Jun. 21. 09:13
URI: http://acta.bibl.u-szeged.hu/id/eprint/59230

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