Nature versus Nurture in Music Recommendations

Steve Krause writes a lengthy review / overview of two different approaches to music recommendations: Pandora and Last.fm. As he sees it, Pandora‘s algorithm-based approach is equal to the nature school of thought while Last.fm‘s behaviour-based approach is equal to the nurture school of thought.

Algorithmically, Pandora versus Last.fm is something like the nature versus nurture debate. Taking the nature side, Pandora’s recommendations are based on the inherent qualities of the music. Give Pandora an artist or song, and it will find similar music in terms of melody, harmony, lyrics, orchestration, vocal character and so on. Pandora likes to call these musical attributes “genes” and its database of songs, classified against hundreds of such attributes, the “Music Genome Project.”

On the nurture side (as in, it’s all about the people around you), Last.fm is a social recommender. It knows little about songs’ inherent qualities. It just assumes that if you and a group of other people enjoy many of the same artists, you will probably enjoy other artists popular with that group.

Like Last.fm, most music-discovery systems have been social recommenders, also known as collaborative filters. Although much of the academic work in the area has focused on improving the matching algorithms, Last.fm’s innovation has been in improving the data the algorithms work on. Last.fm does so by providing users an optional plug-in that automatically monitors your media-player software so that whatever you listen to—whether it came from Last.fm or not—can be incorporated into your Last.fm profile and thus be used as the basis for recommendations. Compared to relying on users to manually provide preferences, this automatic and comprehensive data capture leads to far better grist for the data mill.

I don’t have any experience with either music-recommendation system, but I love the way Krause connects software product design, data mining of enormous sets and basic psychology so people can understand the respective approaches. To me, this is one of the finest things an expert can do - make a subject approachable and comprehensible to a wider, general audience.

For some background on the N-vs-N expression, check out the nature-versus-nurture wikipedia entry.