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Computational Vision and Bio Inspired Computing pp 55–67Cite as

Comprehensive Study on Usage of Multi Objectives in Recommender Systems

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Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 28))

Abstract

Recommender systems have changed its purview from prediction accuracy oriented to finding more relevant and useful recommendations to user. “Usefulness” of items are different in different applications. This paper summarizes the works that have been done in this direction. Personalization, context awareness, multiple objectives of recommendations and evaluation metrics are reviewed in this paper.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, Amrita University, Coimbatore, India

    M. Sruthi, Sini Raj Pulari & Ramesh Gowtham

Authors
  1. M. Sruthi
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  2. Sini Raj Pulari
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  3. Ramesh Gowtham
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Corresponding author

Correspondence to M. Sruthi .

Editor information

Editors and Affiliations

  1. Karunya University , Coimbatore, Tamil Nadu, India

    D. Jude Hemanth

  2. RVS Technical Campus, Coimbatore, Tamil Nadu, India

    S. Smys

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Sruthi, M., Pulari, S.R., Gowtham, R. (2018). Comprehensive Study on Usage of Multi Objectives in Recommender Systems. In: Hemanth, D., Smys, S. (eds) Computational Vision and Bio Inspired Computing . Lecture Notes in Computational Vision and Biomechanics, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-319-71767-8_5

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  • DOI: https://doi.org/10.1007/978-3-319-71767-8_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71766-1

  • Online ISBN: 978-3-319-71767-8

  • eBook Packages: EngineeringEngineering (R0)

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