A recommender system for user matching in networked music interactions = A machine learning-based recommender system for user matching in networked music interactions

Title: A recommender system for user matching in networked music interactions Abstract: Due to the social distancing countermeasures recently enforced during the COVID19 pandemic, a lot of effort is being dedicated to provide online support for the daily activities of musicians, composers, music teachers and students. Several web-based applications are being developed with the aim of supporting remote musical interactions in an easy, fast and intuitive way for musicians of all levels. In such applications, the integration of recommendation and match-making functionalities are of pivotal importance to allow users to find and get in touch with other musicians and to collaborate with them for musical content creation online. The aim of this thesis project is the development of a recommendation system capable of providing suggestions on similarities between musicians based on their musical production.