Personalizing self-organizing music spaces with anchors: design and evaluation

We propose and evaluate a system for content-based visualization and exploration of music collections. The system is based on a modification of Kohonen’s Self-Organizing Map algorithm and allows users to choose the locations of clusters containing acoustically similar tracks on the music space. A user study conducted to evaluate the system shows that the possibility of personalizing the music space was perceived as difficult. Conversely, the user study and objective metrics derived from users’ interactions with the interface demonstrate that the proposed system helped individuals create playlists faster and, under some circumstances, more effectively. We believe that personalized browsing interfaces are an important area of research in Multimedia Information Retrieval, and both the system and user study contribute to the growing work in this field.