An Improved CURE Algorithm - Intelligence Science II Third IFIP TC 12 International Conference, ICIS 2018
Conference Papers Year : 2018

An Improved CURE Algorithm

Abstract

CURE algorithm is an efficient hierarchical clustering algorithm for large data sets. This paper presents an improved CURE algorithm, named ISE-RS-CURE. The algorithm adopts a sample extraction algorithm combined with statistical ideas, which can reasonably select sample points according to different data densities and can improve the representation of sample sets. When the sample set is extracted, the data set is divided at the same time, which can help to reduce the time consumption in the non-sample set allocation process. A selection strategy based on partition influence factor is proposed for the selection of representative points, which comprehensively considers the overall correlation between the data in the region where a representative point is located, so as to improve the rationality of the representative points. Experiments show that the improved CURE algorithm proposed in this paper can ensure the accuracy of the clustering results and can also improve the operating efficiency.
Fichier principal
Vignette du fichier
474230_1_En_11_Chapter.pdf (804.07 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-02118834 , version 1 (03-05-2019)

Licence

Identifiers

Cite

Mingjuan Cai, Yongquan Liang. An Improved CURE Algorithm. 2nd International Conference on Intelligence Science (ICIS), Nov 2018, Beijing, China. pp.102-111, ⟨10.1007/978-3-030-01313-4_11⟩. ⟨hal-02118834⟩
72 View
444 Download

Altmetric

Share

More