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Recommender Systems

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Introduction to Data Science

Part of the book series: Undergraduate Topics in Computer Science ((UTICS))

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Abstract

In this chapter, we will see what are recommender systems , how they work, and how they can be implemented.

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Notes

  1. 1.

    http://www.pandora.com/.

  2. 2.

    http://grouplens.org/datasets/movielens/.

References

  1. G. Shani, A. Gunawardana, A survey of accuracy evaluation metrics of recommendation tasks. in J. Mach. Learn. Res., 10:2935–2962, 2009

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  2. F. Ricci, L. Rokach, B. Schapira, in Recommender Systems Handbook (Springer, 2015).

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Acknowledgements

This chapter was co-written by Santi Seguí and Eloi Puertas

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Authors and Affiliations

  1. Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain

    Laura Igual & Santi Seguí

Authors
  1. Laura Igual
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  2. Santi Seguí
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Corresponding author

Correspondence to Laura Igual .

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Igual, L., Seguí, S. (2017). Recommender Systems. In: Introduction to Data Science. Undergraduate Topics in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-50017-1_9

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  • DOI: https://doi.org/10.1007/978-3-319-50017-1_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50016-4

  • Online ISBN: 978-3-319-50017-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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