Knowledge-Based Music Recommendation: Models, Algorithms and Exploratory Search
PHD THESIS In Partial Fulfilment of the Requirements for the Degree of Doctor of Philosophy from Sorbonne University Specialization: Data Science Knowledge-based Music Recommendation: Models, Algorithms and Exploratory Search Pasquale LISENA Defended on 11/10/2019 before a committee composed of: Reviewer Michel BUFFA, Université Côte d’Azur, INRIA, Sophia Antipolis, France Reviewer Mounia LALMAS, Spotify, University College London, United Kingdom Examiner Gaël RICHARD, TELECOM Paris, France Examiner Tommaso DI NOIA, Politecnico di Bari, Italy Examiner Pietro MICHIARDI, EURECOM, Sophia Antipolis, France Thesis Director Benoit HUET, EURECOM, Sophia Antipolis, France Thesis Co-Director Raphäel TRONCY, EURECOM, Sophia Antipolis, France Dedicated to my family Acknowledgements Firstly, I would like to sincerely thank my advisor Raphäel Troncy, for having strongly wanted me to start this PhD, for having directed and guided my research, for having constantly given value and importance to my work, and for having shared with me goals and responsibilities. I would like to thank the members of my research group for their feedback and cooperation, in particular Enrico Palumbo, which shared with me most of this journey. An acknowledgement goes to the members of the DOREMUS project, which it was a pleasure to work with. I would like to thank also the research group of VU Amsterdam which welcomed me in early 2019 in their vibrant research environment, and in particular Frank van Harmelen, Albert Meroño Peñuela and Ilaria Tiddi. A very special gratitude goes out to all colleagues at EURECOM which contributed to create a pleasant work environment, with a special thank to those that have become genuine friends for me here in France.
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