Ruiqing Hong

BZ-optimized K-Medoids cluster: A hybrid model for scalable and adaptive big data segmentation

The increasing volume, diversity, and complexity of Big Data require clustering techniques capable of handling high-dimensional, noisy, and heterogeneous datasets while maintaining scalability and robustness. This study proposes a BZ-Optimized K-Medoids Clustering Algorithm (BZ-KMedoids) that integrates fuzzy membershi...