| Title: | Music Recommendation Database |
| Duration: | One Semester |
| Responsible TA: | Nicolas Jones |
| Goals: | Creating a music recommender system. Setup a music database as a first step. |
| Keywords: | data collection, recommender systems |
| Abstract: |
Recommender systems (RS) have started becoming popular to help users overcome the information overload problems on internet. Today’s trends of Web 2.0 and the emergence of social interactions, where content is created and shared by users, have lead to new contexts where RS are used such as music. The goal of the project is create a music database, usable for a future recommender system. The first challenge will be to organise and classify a comprehensive collection of music files (+10000 songs), leading to the second challenge ofcompleting the meta-data of each track, such as artist, track, album, etc. (through automated querying of the Gracenote database, or other) leading to the establishement of a rich and complete music database. The developpment should include the interface for listening and importing new songs. Finally, if time permits, the project will include the setting up of a basic music recommender. Based on the remaining time, the project can be extended such as to for example include data mining goals for add taging values to the songs. Many music websites provide web services for consulting tags related to tracks, and this could be used to create a second level abstraction, an ontology, for enhancing music recommendations. |
| Project Results: |
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| Required Skills |
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