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The PartyVote Music Library Visualization System

The PartyVote Music Library Visualization System. No play list, no DJ, no problem! Nadia Rashid, David Sprague, and Fuqu Wu. Motivation. Previous Literature. Jukola Pandora MUSICtable. Visualization Goals. Co-present music collaboration for closely knit social groups Lightweight

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The PartyVote Music Library Visualization System

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  1. The PartyVote Music Library Visualization System No play list, no DJ, no problem! Nadia Rashid, David Sprague, and Fuqu Wu

  2. Motivation

  3. Previous Literature • Jukola • Pandora • MUSICtable

  4. Visualization Goals • Co-present music collaboration for closely knit social groups • Lightweight • Enable system understanding • Optimal for participants

  5. System Usage • 10-20 participants • 500+ songs • 6 hours of non-repeating music.

  6. General Overview

  7. Voting & Music Selection • All songs start with weighting of 0 • Participants vote for a song/album or artist • Weight = Weight + (1/# of songs) • Similar songs also affected by votes. • High dimensional cluster/hull defined by songs with weight > 0 • Songs in this cluster are potentially played.

  8. Vote Clustering

  9. Vote Clustering

  10. Vote Clustering

  11. The Interface

  12. Interface part 2

  13. Challenges • MDS and Convex Hull/Clustering Algorithm. • Lots and LOTS of coding • Evaluation and distance metric tweaking

  14. Visualization Goals Revisited • Co-present music collaboration for closely knit social groups ✔ • Lightweight ✔ • Enable system understanding ✔ • Optimal for participants ✔

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