Title
Online One Pass Clustering Of Data Streams Based On Growing Neural Gas And Fuzzy Inference Systems
Abstract
The clustering of big data streams has become a challenging task due to time and space constraints of the hardware and decreasing accuracy when the dimensionality of input data grows in time. In this paper, fuzzy growing neural gas is introduced, an online fuzzy approach for clustering data streams based on the growing neural gas algorithm, by adopting more restrictive criteria for selecting the winner nodes in the topological graph constructed at each iteration of the algorithm. The algorithm is tested on public datasets, and the results show improvements over existing clustering methods.
Year
DOI
Venue
2021
10.1111/exsy.12736
EXPERT SYSTEMS
Keywords
DocType
Volume
data stream clustering, fuzzy logic, growing neural gas (GNG), topology preservation
Journal
38
Issue
ISSN
Citations 
7
0266-4720
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Ali Mahmoudabadi100.34
Marjan Kuchaki Rafsanjani27616.18
Mohammad M. Javidi37112.98