A new approach data processing: density-based spatial clustering of applications with noise (DBSCAN) clustering using game-theory

Due to the unpredictable growth of data in various fields, rapid clustering of big data is seriously needed in order to identify the hidden structure of data and discover the relationships between objects. Among clustering methods, density-based clustering methods have an acceptable processing speed...

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Bibliographic Details
Published in:	Soft computing (Berlin, Germany) Vol. 29; no. 3; pp. 1331 - 1346
Main Authors:	Kazemi, Uranus, Soleimani, Seyfollah
Format:	Journal Article
Language:	English
Published:	Heidelberg Springer Nature B.V 01.02.2025
Subjects:	Accuracy Algorithms Big Data Clustering Data compression Data mining Data points Data processing Datasets Density Efficiency Fluid dynamics Game theory Massive data points Methods Optimization Parameter sensitivity Spatial data Synthetic data
ISSN:	1432-7643, 1433-7479
Online Access:	Get full text
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