Learning Self-Refined Organizing Map for Efficient Imbalanced Streaming Data Clustering

The proposed Learning Self-Refined Organizing Map (LSROM) algorithm efficiently handles the imbalanced streaming data clustering problem by leveraging an advanced Self-Organizing Map (SOM) to represent the global data distribution, refine the partition, and guide the merging of micro-clusters.