D3.2 – Predictive Analytics and Recommendation Framework V2
D3.2 – Predictive analytics and recommendation framework v2 Αugust 31st, 2019 Authors: Thomas Lidy (MMAP), Adrian Lecoutre (MMAP), Khalil Boulkenafet (MMAP), Manos Schinas (CERTH), Christos Koutlis (CERTH), Symeon Papadopoulos (CERTH) Contributor/s: Vasiliki Gkatziaki (CERTH), Emmanouil Krasanakis (CERTH), Polychronis Charitidis (CERTH) Deliverable Lead Beneficiary: MMAP This project has been co-funded by the HORIZON 2020 Programme of the European Union. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use, which may be made of the information contained therein. Multimodal Predictive Analytics and Recommendation Services for the Music Industry 2 Deliverable number or D3.2 Predictive analytics and recommendation framework supporting document title Type Report Dissemination level Public Publication date 31-08-2019 Author(s) Thomas Lidy (MMAP), Adrian Lecoutre (MMAP), Khalil Boulkenafet (MMAP), Manos Schinas (CERTH), Christos Koutlis (CERTH), Symeon Papadopoulos (CERTH) Contributor(s) Emmanouil Krasanakis (CERTH), Vasiliki Gkatziaki (CERTH), Polychronis Charitidis (CERTH) Reviewer(s) Rémi Mignot (IRCAM) Keywords Track popularity, artist popularity, music genre popularity, track recognition estimation, emerging artist discovery, popularity forecasting Website www.futurepulse.eu CHANGE LOG Version Date Description of change Responsible V0.1 25/06/2019 First deliverable draft version, table of contents Thomas Lidy (MMAP) V0.2 18/07/2019 Main contribution on track recognition estimation
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