ArtBeats makes the Philadelphia Museum of Art’s collection more accessible by leveraging a visitor’s taste in music to direct them to pieces they may connect with based on a collection of crowdsourced, relational, music data. First, ArtBeats learns about the user's musical preference by asking them to select their favorite genres of music. The application pairs their tastes with art throughout the PMA’s collection associated with these genres. The user can then view these pieces to start their journey through the museum.

Each piece in the collection has a musical profile crowdsourced from ArtBeats users. This profile is formed by encouraging each user to engage with the pieces of art by choosing songs (pulled from Spotify) they feel pair well with or helps tell the story of the piece. The musical profile of each piece is an interactive playlist where users can add new songs or like songs already listed. You can also listen to each associated song through the Spotify app. As users engage with each piece, ArtBeats learns from this information and updates the musical genres associated with each piece. These associations are then compared against the musical profile of the user to predict which art the user will have the strongest preference towards.

As the user walks through the museum, ArtBeats will track the user's movement through the galleries. The user can click on any of these gallery locations to pull up a list view of the pieces currently in the gallery. Pieces that match the user’s genre preferences are emphasized with a star icon in the bottom right corner of the image. In addition, the user will have a recommendation profile that is constantly updated with new pieces as their own and others’ user data is contributed to artworks’ profiles.

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