Evolving Gaussian on-line clustering in social network analysis
作者：
Highlights：
• Evolving clustering algorithm based on the Gaussian probability distribution.
• Online single-pass clustering with adding and merging mechanisms.
• Tested on known datasets Iris and Breast Cancer Wisconsin.
• Competitive results compared to established machine learning methods.
• Example on real data of Twitter account activity.
摘要
•Evolving clustering algorithm based on the Gaussian probability distribution.•Online single-pass clustering with adding and merging mechanisms.•Tested on known datasets Iris and Breast Cancer Wisconsin.•Competitive results compared to established machine learning methods.•Example on real data of Twitter account activity.
论文关键词：Evolving clustering,Twitter data analysis,Online method,Gaussian probability
论文评审过程：Received 25 October 2021, Revised 13 April 2022, Accepted 13 June 2022, Available online 22 June 2022, Version of Record 30 June 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.117881
