Different algorithms’ performance across 8 cores.

<div><p>To address the instability and performance issues of the classical K-Means algorithm when dealing with massive datasets, we propose SOSK-Means, an improved K-Means algorithm based on Spark optimization. SOSK-Means incorporates several key modifications to enhance the clustering p...

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Bibliographic Details
Main Author:	Yongan Feng (7345193) (author)
Other Authors:	Jiapeng Zou (20469071) (author), Wanjun Liu (637552) (author), Fu Lv (17708560) (author)
Published:	2024
Subjects:	Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified reduce computation time experimental results show directed acyclic graph enhancing clustering accuracy best initial centers improved clustering performance means algorithm based initial centers clustering process improved k performance issues optimize performance xlink "> weighted max weighted jump spark optimization spark framework reduces sensitivity performed using overall efficiency min distance means incorporates means algorithm massive datasets jump pointers iteration process incorporating weights identify clusters farther apart distributed strategies distributed k classical k calculate distances bank approach approach improves
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Different algorithms’ performance across 8 cores.

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