Chen-Xi Zheng

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

A BZ-Optimized K-Medoids Clustering Algorithm that integrates fuzzy membership modelling, BZ-based medoid optimization, and distributed processing within a unified clustering framework is proposed that achieved superior clustering quality while maintaining scalability for large and heterogeneous Big Data environments.