Different Types of Search Algorithms for Rough Sets
| Autor: | Tamás Mihálydeák, Dávid Nagy, László Aszalós |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Information Systems and Management
Theoretical computer science Relation (database) Computer science 05 social sciences 050301 education 02 engineering and technology Management Science and Operations Research Object (computer science) Partition (database) Theoretical Computer Science Set (abstract data type) Search algorithm 0202 electrical engineering electronic engineering information engineering Computer Science (miscellaneous) Information system 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Rough set Electrical and Electronic Engineering Cluster analysis 0503 education Software |
| Zdroj: | Acta Cybernetica. 24:105-120 |
| ISSN: | 0324-721X |
| DOI: | 10.14232/actacyb.24.1.2019.8 |
| Popis: | 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 settwo 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 is needed to bestated, then all the objects that are indiscernible from the given object must be taken into consideration. The indiscernibility relation is an equivalencerelation which represents 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 the possible usage of the correlation clusteringin rough set theory was investigated. In this paper the authors show how different types of search algorithms affect the set approximation. |
| Databáze: | OpenAIRE |
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