A software repository, a place where reusable components are stored and searched for, is a key ingredient for instituting and popularizing software reuse. It is vital that a software repository should be well-organized and provide efficient tools for developers to locate reusable components that meet their requirements. The growing hierarchical self-organizing map (GHSOM), an unsupervised learning neural network, is a powerful data mining technique for the clustering and visualization of large and complex data sets. The resulting maps, serving as retrieval interfaces, can be beneficial to developers in obtaining better insight into the structure of a software repository and increasing their understanding of the relationships among software components. The GHSOM, which is an improvement over the basic self-organizing map (SOM), can adapt its architecture during its learning process and expose the hierarchical structure that exists in the original data. In this paper, we demonstrate the potential of the GHSOM for the organization and visualization of a collection of reusable components stored in a software repository, and compare the results with the ones obtained by using the traditional SOM.