On a two-stage progressive clustering algorithm with graph-augmented density peak clustering-Reference-Cited by-同舟云学术

On a two-stage progressive clustering algorithm with graph-augmented density peak clustering

Published:2022-02 Issue: Volume:108 Page:104566
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Niu Xinzheng,Zheng Yunhong,Liu Wuji^ORCID,Wu Chase Q.

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference48 articles.

1. Automated determination of the input parameter of DBSCAN based on outlier detection;Akbari,2016

2. An effective density-based clustering and dynamic maintenance framework for evolving medical data streams;Al;Int. J. Med. Inform.,2019

3. Alazeez, A., Jassim, S., H, Du, 2017. EDDS: an enhanced density-based method for clustering data streams. In: 46th International Conference on Parallel Processing Workshops (ICPPW 2017). pp. 103–112.

4. MuDi-Stream: a multi density clustering algorithm for evolving data stream;Amini;J. Netw. Comput. Appl.,2016

5. An evolutionary algorithm for clustering data streams with a variable number of clusters;Andrade;Expert Syst. Appl.,2017

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