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Recommender Systems Handbook pp 1–34Cite as

Recommender Systems: Introduction and Challenges

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Abstract

Recommender Systems (RSs) are software tools and techniques that provide suggestions for items that are most likely of interest to a particular user. In this introductory chapter, we briefly discuss basic RS ideas and concepts. Our main goal is to delineate, in a coherent and structured way, the chapters included in this handbook. Additionally, we aim to help the reader navigate the rich and detailed content that this handbook offers.

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Notes

  1. 1.

    This issue, convincing the user to accept a recommendation, is discussed again when we explain the difference between predicting the user interest in an item and the likelihood that the user will select the recommended item.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano, Italy

    Francesco Ricci

  2. Department of Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Lior Rokach & Bracha Shapira

Authors
  1. Francesco Ricci
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  2. Lior Rokach
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  3. Bracha Shapira
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Correspondence to Francesco Ricci .

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Editors and Affiliations

  1. Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano - Bozen, Italy

    Francesco Ricci

  2. Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Lior Rokach

  3. Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Bracha Shapira

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Ricci, F., Rokach, L., Shapira, B. (2015). Recommender Systems: Introduction and Challenges. In: Ricci, F., Rokach, L., Shapira, B. (eds) Recommender Systems Handbook. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7637-6_1

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  • DOI: https://doi.org/10.1007/978-1-4899-7637-6_1

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4899-7636-9

  • Online ISBN: 978-1-4899-7637-6

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