Skip to main content
SpringerLink
Log in
Book cover

International Conference on Practical Applications of Agents and Multi-Agent Systems

PAAMS 2017: Trends in Cyber-Physical Multi-Agent Systems. The PAAMS Collection - 15th International Conference, PAAMS 2017 pp 214–220Cite as

Recommender System Based on Collaborative Filtering for Spotify’s Users

  • Conference paper
  • First Online:

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 619))

Abstract

In recent years, with the rise of streaming services like Netflix or Spotify, recommender systems are becoming more and more necessary. The success of Spotify’s Discover Weekly, a music recommender system that suggests new songs to users every week, confirms the need to implement these recommender systems. In this paper we propose a methodology based on collaborative filtering to recommend music for Spotify’s users from an ordered list of the most played songs over a period of time.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    https://www.spotify.com.

  2. 2.

    https://developer.spotify.com/web-api/.

  3. 3.

    http://ocelma.net/MusicRecommendationDataset/lastfm-1K.html.

  4. 4.

    http://www.last.fm.

  5. 5.

    https://nodejs.org.

  6. 6.

    https://www.mongodb.com.

References

  1. Bateira, J.L.: Spotify-ed-music recommendation and discovery in spotify (2014)

    Google Scholar 

  2. Celma, O.: Music Recommendation and Discovery in the Long Tail. Springer, Heidelberg (2010)

    Google Scholar 

  3. Germain, A., Chakareski, J.: Spotify me: Facebook-assisted automatic playlist generation. In: 2013 IEEE 15th International Workshop on Multimedia Signal Processing (MMSP), pp. 025–028. IEEE (2013)

    Google Scholar 

  4. Pichl, M., Zangerle, E., Specht, G.: # nowplaying on # spotify: leveraging spotify information on twitter for artist recommendations. In: International Conference on Web Engineering, pp. 163–174. Springer (2015)

    Google Scholar 

  5. Sarwar, B., Karypis, G., Konstan, J., Riedl, J.: Item-based collaborative filtering recommendation algorithms. In: Proceedings of the 10th International Conference on World Wide Web, pp. 285–295. ACM (2001)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computing and Automation, University of Salamanca, Plaza de los Caidos s/n, 37008, Salamanca, Spain

    Javier Pérez-Marcos & Vivian López Batista

Authors
  1. Javier Pérez-Marcos
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vivian López Batista
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Javier Pérez-Marcos .

Editor information

Editors and Affiliations

  1. Departamento de Informática y Automática, Facultad de Ciencias, Universidad de Salamanca, Salamanca, Spain

    Fernando De la Prieta

  2. GECAD Instituto Superior de Engenharia do Porto, Porto, Portugal

    Zita Vale

  3. Department of Informática, Universidade de Lisboa Faculdade de Ciências, Lisboa, Portugal

    Luis Antunes

  4. Facultad de Ciencias, Departamento de Informática y Automática, Salamanca, Spain

    Tiago Pinto

  5. School of Computer Science, Dartmouth College, Hanover, New Hampshire, USA

    Andrew T. Campbell

  6. Departamento de Sistemas Informáticos y Computación, Universidad Politecnica de Valencia, Valencia, Spain

    Vicente Julián

  7. University of Aveiro, Institute of Electronics and Telematics Engineering, Aveiro, Portugal

    Antonio J.R. Neves

  8. Departamento de Informática y Automática, Facultad de Ciencias, University of Salamanca, Salamanca, Salamanca, Spain

    María N. Moreno

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Pérez-Marcos, J., López Batista, V. (2018). Recommender System Based on Collaborative Filtering for Spotify’s Users. In: De la Prieta, F., et al. Trends in Cyber-Physical Multi-Agent Systems. The PAAMS Collection - 15th International Conference, PAAMS 2017. PAAMS 2017. Advances in Intelligent Systems and Computing, vol 619. Springer, Cham. https://doi.org/10.1007/978-3-319-61578-3_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-61578-3_22

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61577-6

  • Online ISBN: 978-3-319-61578-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation