Towards semi-supervised ensemble clustering using a new membership similarity measure-Reference-Cited by-同舟云学术

Towards semi-supervised ensemble clustering using a new membership similarity measure

Published:2023-05-28 Issue:4 Volume:64 Page:764-771
ISSN:0005-1144
Container-title:Automatika
language:en
Short-container-title:Automatika

Author:

Li Wenjun¹,Li Ting²,Mojarad Musa³

Affiliation:

1. School of Software and Service Outsourcing, Suzhou Vocational Institute of Industrial Technology, Suzhou, People’s Republic of China

2. Suzhou Blueprint Smart City Technology Co. Ltd, Suzhou, People’s Republic of China

3. Department of Computer Engineering, Firoozabad Branch, Islamic Azad University, Firoozabad, Iran

Funder

Natural Science Foundation of Jiangsu Province

Natural Science Foundation of the Jiangsu Higher Education Institutions of China

Research Funds of Suzhou Vocational Institute of Industrial Technology

Publisher

Informa UK Limited

Subject

General Computer Science,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/00051144.2023.2217601

Reference25 articles.

1. Casas P, Mazel J, Owezarski P. MINETRAC: mining flows for unsupervised analysis & semi-supervised classification. In: 2011 23rd International Teletraffic Congress (ITC). IEEE; 2011, September. p. 87–94.

2. Semi-supervised extensions of multi-task tree ensembles

3. Yang T, Pasquier N, Precioso F. Ensemble clustering based semi-supervised learning for revenue accounting workflow management. In: DATA. 2020, July. p. 283–293.

4. Command-Filtered Adaptive Fuzzy Control for Switched MIMO Nonlinear Systems with Unknown Dead Zones and Full State Constraints

5. Enhancing Time Series Clustering by Incorporating Multiple Distance Measures with Semi-Supervised Learning

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