文章基本信息

标题：A Novel Grid-Based Clustering Algorithm
本地全文：下载
作者：Artur Starczewski ; Magdalena M.Scherer ; Wojciech Książek 等
期刊名称：Journal of Artificial Intelligence and Soft Computing Research
电子版ISSN：2083-2567
出版年度：2021
卷号：11
期号：4
页码：319-330
DOI：10.2478/jaiscr-2021-0019
语种：English
出版社：Walter de Gruyter GmbH
摘要：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 kdist function which computes the distance between each element of a dataset and its kth nearest neighbor. Experimental results have been obtained for several different datasets and they confirm a very good performance of the newly proposed method.
关键词：data mining;grid-based clustering;grid structure