Data Clustering and Visualization with Recursive Goemans-Williamson MaxCut Algorithm

• URL: http://arxiv.org/abs/2408.07763v1
• Date: Wed, 14 Aug 2024 18:30:57 GMT
• Title: Data Clustering and Visualization with Recursive Goemans-Williamson MaxCut Algorithm
• Abstract summary: We introduce a novel modification to the classical Goemans-Williamson MaxCut algorithm, offering improved performance in vectorized data clustering tasks. Our methods provide advantages in both computational efficiency and clustering accuracy, substantiated through comprehensive experiments.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this article, we introduce a novel recursive modification to the classical Goemans-Williamson MaxCut algorithm, offering improved performance in vectorized data clustering tasks. Focusing on the clustering of medical publications, we employ recursive iterations in conjunction with a dimension relaxation method to significantly enhance density of clustering results. Furthermore, we propose a unique vectorization technique for articles, leveraging conditional probabilities for more effective clustering. Our methods provide advantages in both computational efficiency and clustering accuracy, substantiated through comprehensive experiments.

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