A Novel Grid-Based Clustering Algorithm

Data clustering is an important method used to discover naturally occurring structures in datasets. One of the most popular approaches is the grid-based concept of clustering algorithms. This kind of method is characterized by a fast processing time and it can also discover clusters of arbitrary sha...

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Vydáno v:Journal of Artificial Intelligence and Soft Computing Research Ročník 11; číslo 4; s. 319 - 330
Hlavní autoři: Starczewski, Artur, Scherer, Magdalena M., Książek, Wojciech, Dębski, Maciej, Wang, Lipo
Médium: Journal Article
Jazyk:angličtina
Vydáno: Warsaw Sciendo 01.10.2021
De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
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ISSN:2449-6499, 2449-6499
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Shrnutí:Data clustering is an important method used to discover naturally occurring structures in datasets. One of the most popular approaches is the grid-based concept of clustering algorithms. This kind of method is characterized by a fast processing time and it can also discover clusters of arbitrary shapes in datasets. These properties allow these methods to be used in many different applications. Researchers have created many versions of the clustering method using the grid-based approach. However, the key issue is the right choice of the number of grid cells. This paper proposes a novel grid-based algorithm which uses a method for an automatic determining of the number of grid cells. This method is based on the function which computes the distance between each element of a dataset and its th nearest neighbor. Experimental results have been obtained for several different datasets and they confirm a very good performance of the newly proposed method.
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ISSN:2449-6499
2449-6499
DOI:10.2478/jaiscr-2021-0019