DH-Kmeans: An Improved K-means Clustering Algorithm based on Dynamic Initial Cluster Center Determination and Hierarchical Clustering-Reference-Cited by-同舟云学术

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DH-Kmeans: An Improved K-means Clustering Algorithm based on Dynamic Initial Cluster Center Determination and Hierarchical Clustering

Published:2022-05-04 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD)
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Author:

Zhu Erzhou¹,Wang Zihan¹,Liu Feng¹,Ma Zhujuan²

Affiliation:

1. Anhui University,School of Computer Science and Technology,Hefei,China

2. Hefei University of Economics,School of Artificial Intelligence,Hefei,China

Funder

Natural Science Foundation of Anhui Province

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9775971/9776016/09776225.pdf?arnumber=9776225

Reference9 articles.

1. Data clustering: 50 years beyond K-means

2. An overview of clustering methods

3. Improved K-means algorithm based on density Canopy

4. Gravitational search algorithm and K-means for simultaneous feature selection and data clustering: a multi-objective approach

5. Optimal Clustering Number Determining Algorithm by the New Clustering Method;zhu;Ruan Jian Xue Bao/Journal of Software,2021

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