K-means text clustering based on improved particle swarm optimization

To address the influence of initial cluster center selection on K-means, we propose IPSOK-means, a text clustering method that utilizes improved particle swarm optimization (PSO). IPSOK-means incorporates a self-adjusting inertia weight mechanism to enhance population diversity and exploration capabilities. Experimental results demonstrate that IPSOK-means achieves superior text clustering effectiveness when compared to K-means, SKM, and PSOK-means.