1. Exploiting Recommended Usage Metadata: Exploratory Analyses Xiao Hu, J. Stephen Downie, Andreas Ehmann THE ANDREW W. MELLON FOUNDATION The International Music Information Retrieval Systems Evaluation Lab (IMIRSEL) University of Illinois at Urbana-Champaign

2. Motivation zHuman Use of Music Information Retrieval Systems (HUMIRS) project to identify:  Standardized MIR evaluation tasks  Query documents from real world users’ behaviors User generated usage metadata

3. Usage Metadata z Music Customer reviews on www.epinions.com z Each review is associated with one recommended usage

4. Usage Categories DrivingWaking up Hanging With FriendsGoing to Sleep ListeningCleaning the House RomancingAt Work Reading or StudyingWith Family Getting ready to go outSleeping Exercising zPrepared by epinions.com editors

5. Album Metadata zEach review is for an album album title

6. Research Questions z Q1: What are the relationships between usages and music genres? z Q2: What are the relationships between usages and music artists? z Q3: How are the usages related to each other?

7. Data Facts Number of Usage Categories11 Reviews in Each Usage Categories180 Total Number of Reviews1,980 Number of Genres12 Number of Artists897 Number of Album titles1,372

8. Genre and Usage (1) zGenres: BluesHeavy Metal ClassicalInternational CountryJazz Instrument ElectronicPop Vocal GospelR&B Hardcore/PunkRock & Pop

9. Genre and Usage (2) zDependency analysis:  Pearson’s chi-square dependency test  on each pair of genre and usage (p < 0.001) GenreUsagePearson’s χ 2 ClassicalListening37.613 CountryCleaning the House70.782 ElectronicGoing to Sleep29.127 Hard Core / PunkWaking Up12.536 Jazz InstrumentRomancing123.452 Pop VocalRomancing49.877

10. Artist and Usage (1) zDependency analysis  Binomial exact test  on usages and artists with  10 reviews ArtistUsagep value AFIWaking Up0.03252 Black SabbathAt Work0.00028 Celine DionRomancing0.02499 Dream TheaterListening0.01862 MetallicaWaking Up0.03252 Nirvana_(USA)Going to Sleep0.01862

11. Artist and Usage (2) zUsage Profiles  Usage distributions of 10 most-reviewed artists

12. Clustering on co-occurrences z Some usages appear to be related e.g. “Exercising” and “Cleaning the House” z Q3: Can the usages form meaningful superclasses base on their co-occurrences with genre, artist and album titles?

13. Clusters from genre-usage co-occurrences Romancing Getting ready to go out Exercising Waking up Hanging out with friends At work Driving Listening Going to sleep Reading or studying Cleaning the house Relaxing Stimulating

14. Clusters from artist-usage co-occurrences Going to sleep Listening Reading or studying Romancing At work Exercising Waking up Getting ready to go out Driving Cleaning the house Hanging out with friends Relaxing Stimulating

15. Clusters from album-usage co-occurrences Going to sleep Reading or studying Listening Exercising Waking up At work Cleaning the house Driving Hanging out with friends Getting ready to go out Romancing Relaxing Stimulating

16. To summarize … Stimulating: Exercising, Waking up, At work, Driving, Hanging out with friends, Getting ready to go out Relaxing: Going to sleep, Reading or studying Discrepant:RelaxingStimulatingseparate Listening210 Romancing111 Cleaning the house021

17. Data Limitations zOnly from one website zUsage choices are predefined zSome usages are ambiguous zInterpretations vary across users zOnly one usage per review  can’t see how individual users group usages

18. Conclusions zUsage: another facet of music similarity  Complementary to artist and genre similarity zConsistent superclasses of usages  Meaningful user-generated metadata  New task / query for MIREX zFurther investigation is warranted  Larger scale dataset from multiple websites  Connect to audio features

19. Questions? IMIRSEL Thank you! THE ANDREW W. MELLON FOUNDATION

20. Usage Categories and Counts UsageCountUsageCount Driving1,349Waking up271 Hanging With Friends1,215Going to Sleep269 Listening592Cleaning the House230 Romancing492At Work188 Reading or Studying447With Family35 Getting ready to go out378Sleeping15 Exercising291TOTAL5,772

21. Agenda zMotivation zUsage metadata in www.epinions.com zResearch Questions zAnalysis  Genre and usage  Artist and usage  Clustering on co-occurrences zConclusions

22. Clustering on co-occurrences z Some usages appear to be related e.g. “Exercising” and “Cleaning the House” z Q3: Can the usages form meaningful superclasses base on their co-occurrences with genre, artist and album titles? Facets with multiple usagesnumberreviews Genres121,980 Artists3681,451 Album titles366974