Abstract: As the world of online music grows, tools for helping people find new and interesting music in these extremely large collections become increasingly important. In this tutorial we look at one such tool that can be used to help people explore large music collections: information visualization. We survey the state-of-the-art in visualization for music discovery in commercial and research systems. Using numerous examples, we explore different algorithms and techniques that can be used to visualize large and complex music spaces, focusing on the advantages and the disadvantages of the various techniques. We investigate user factors that affect the usefulness of a visualization and we suggest possible areas of exploration for future research.
This tutorial will be filled with examples (both of code and of commercial and research oriented visualizations).
Justin Donaldson is a PhD candidate at Indiana University School of Informatics, as well as a regular research intern at Strands, Inc. Justin is interested with the analyses and visualizations of social sources of data, such as those that are generated from playlists, blogs, and bookmarks.
Paul Lamere is the Director of Developer Community at The Echo Nest, a research-focused music intelligence startup that provides music information services to developers and partners through a data mining and machine listening platform. Paul is especially interested in hybrid music recommenders and using visualizations to aid music discovery. Paul also authors 'Music Machinery' a blog focusing on music discovery and recommendation.