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A Web System Based on Spotify for the automatic generation of affective playlists

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Cloud Computing, Big Data & Emerging Topics (JCC-BD&ET 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1291))

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Abstract

The online music streaming providers offer powerful personalization tools for recommending songs to their registered users. These tools are usually based on users’ listening histories and tastes, but ignore other contextual variables that affect users while listening to music, for example, the user’s mood. In this paper, a Web-based system for generating affective playlists that regulate the user’s mood is presented. The system has been implemented integrating resources and data offered by Spotify through its service platform, and the playlists generated are directly published in the user’s Spotify account. Internally, the emotions play a relevant role in the processes of cataloguing songs and making personalized music recommendations. Novel affective computing solutions are combined with traditional information retrieval and artificial intelligence techniques in order to solve these complex engineering problems. Besides, these solutions consider users’ collaboration as a first-class element in an attempt to improve affective recommendations.

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Acknowledges

This work has been supported by the TIN2017-84796-C2-2-R and RTI2018-096986-B-C31 projects, granted by the Spanish Ministerio de Economía y Competitividad, and the DisCo-T21-20R and Affective-Lab-T60-20R projects, granted by the Aragonese Government.

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Authors and Affiliations

  1. Computer Science and Systems Engineering Department, Zaragoza University of Zaragoza, María de Luna, 1, Ada Byron Building, Zaragoza, Spain

    Pedro Álvarez, Jorge García de Quirós & Sandra Baldassarri

Authors
  1. Pedro Álvarez
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  2. Jorge García de Quirós
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  3. Sandra Baldassarri
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Corresponding author

Correspondence to Pedro Álvarez .

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Editors and Affiliations

  1. III-LIDI, Facultad de Informatica, Universidad Nacional de La Plata and CIC, La Plata, Argentina

    Enzo Rucci

  2. III-LIDI, Facultad de Informática, Universidad Nacional de La Plata and CIC, La Plata, Argentina

    Marcelo Naiouf

  3. III-LIDI, Facultad de Informática, Universidad Nacional de La Plata and CIC, La Plata, Argentina

    Franco Chichizola

  4. III-LIDI, Facultad de Informática, Universidad Nacional de La Plata and CIC, La Plata, Argentina

    Laura De Giusti

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Álvarez, P., García de Quirós, J., Baldassarri, S. (2020). A Web System Based on Spotify for the automatic generation of affective playlists. In: Rucci, E., Naiouf, M., Chichizola, F., De Giusti, L. (eds) Cloud Computing, Big Data & Emerging Topics. JCC-BD&ET 2020. Communications in Computer and Information Science, vol 1291. Springer, Cham. https://doi.org/10.1007/978-3-030-61218-4_9

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  • DOI: https://doi.org/10.1007/978-3-030-61218-4_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61217-7

  • Online ISBN: 978-3-030-61218-4

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