/vire

Web system able to "intelligently" recommend – by exposing a SPARQL endpoint – vinyl music records according to various criteria: user preferences , past song purchases on various music stores, playlists – available online via music streaming services – and/or locally – for instance, by uploading a JSPF/XSPF document.

vire

Problem description:

Build a (micro-)service Web system able to "intelligently" recommend – by exposing a SPARQL endpoint – vinyl music records according to various criteria:

  • user preferences (specified via controlled natural language constructs such as:

"I always like/love/prefer classical music, especially opera music by Rossini or Verdi and performed by Angela Gheorghiu or Juan Diego Flórez; I sometimes like progressive rock and post-rock; I like only metal albums released before 2000; I always dislike/hate rap and hip-hop; I dislike songs produced by Flood in the last 25 years"

  • past song purchases on various music stores
  • playlists – available online via music streaming services: Last.fm and alternative solutions – and/or locally – for instance, by uploading a JSPF/XSPF document.

The playlists could be created by the user or shared by her/his virtual "friends" (consider at least one social network).

The system will use several music-related knowledge models (e.g., Music Ontology or MusicRecording concept from schema.org) and available public resources: Discogs, MusicBrainz, Musicmoz Music Styles.

Design and arhitecture

  • Arhitecture of the web application:
  • OpenAPI specification regarding the REST API – or, alternatively, a schema for the GraphQL API (Open API - available in the technical report), all of them can be found in the report
  • Technical report: https://stativacamelia.github.io/vire/
  • Project progress: