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Recommender Systems: Techniques, Applications, and Challenges

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Recommender Systems Handbook

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 in this handbook. Additionally, we aim to help the reader navigate the rich and detailed content that this handbook offers.

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Authors and Affiliations

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

    Francesco Ricci

  2. Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beersheba, Israel

    Lior Rokach & Bracha Shapira

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  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, Bozen-Bolzano, Italy

    Francesco Ricci

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

    Lior Rokach

  3. Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Bracha Shapira

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Ricci, F., Rokach, L., Shapira, B. (2022). Recommender Systems: Techniques, Applications, and Challenges. In: Ricci, F., Rokach, L., Shapira, B. (eds) Recommender Systems Handbook. Springer, New York, NY. https://doi.org/10.1007/978-1-0716-2197-4_1

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