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Jun, 2022
SECLEDS: 基于多个中心点和中心点投票法的数据流序列聚类算法
SECLEDS: Sequence Clustering in Evolving Data Streams via Multiple Medoids and Medoid Voting
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Azqa Nadeem, Sicco Verwer
TL;DR
该论文提出了一种流式k-medoids算法的变种SECLEDS,它使用多个质心聚类,通过中心投票方案处理数据流中的概念漂移,以实现高效的序列聚类,同时提高聚类的质量和稳定性,并证明了其在网络流量聚类中的较高性能。
Abstract
sequence clustering
in a streaming environment is challenging because it is computationally expensive, and the sequences may evolve over time.
k-medoids
or Partitioning Around Medoids (PAM) is commonly used to cl
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