Evaluation of cultural similarity in playlist generation Mariusz Kleć Polish-Japanese Institute of Information Technology in Warsaw, Poland

Schedule of my presentation 1. Introduction 2. Playlists 3. Cultural similarity 4. Playlist Generator software 5. Experiment 6. Results 7. Questions / discussion

Introduction Large music collections

Playlists definition

Playlists Automatic playlist generation user initial action playlist generation Query-by-example

Playlists playlists created by query-by-example method

…how often particular artists co-occur on the same web pages… Cultural similarity artist similarity

Cultural similarity Scoring functions D. P.W. Ellis, B. Whitman, A. Berenzweig, S. Lawrence. The quest for ground truth in musical artist similarity. Proceedings of the International Conference on Music Information Retrieval. 170–7, 2002 Geleijnse, G., and J. Korst. Web-based artist categorization. Proceedings of the International Conference on Music Information Retrieval. 266–71, 2006

Playlist Generator software Author’s software

Playlist Generator software similarity matrix

Playlist Generator software making playlist using similarity matrix Higher similarity Lower similarity Queen 2 Diana Krall 3 Cranberries 4 Aerosmith 5 Bon Jovi 6 Rod Steward 7 Bach 8 The Rolling Stones 9 Tina Turner 10 Phil Collins1

Experiment What’s the goal?

Experiment details A playlist

Experiment details

Results Software and people’s playlist similarities

Results Average value of similarities between playlists

Results summary Automatic playlists generation process that incorporates f2 function is more effective as regards people’s expectation about artists similarity

Questions