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Empfehlungssysteme

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Handbuch Digitale Wirtschaft

Part of the book series: Springer Reference Wirtschaft ((SRW))

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Zusammenfassung

Empfehlungssysteme stellen heute eine zentrale Komponente vieler Online-Plattformen dar, die bei Online-Shops und vielen anderen Anwendungen häufig zum Einsatz kommt. Ziel ist es, dem Kunden entsprechend seinen persönlichen Präferenzen Produkte oder andere Artikel vorzuschlagen, die für ihn von Interesse sind und potenziell zu einem Kauf oder generell zur Nutzung führen. Empfehlungssysteme haben eine erhebliche wirtschaftliche Bedeutung, da sie in vielen Fällen zu einem signifikanten Anteil zu Erfolgsfaktoren wie Click-through-Raten oder Käufen beitragen. Wir stellen in diesem Kapitel die unterschiedlichen Ansätze zur automatisierten Empfehlungsgebung vor und beschreiben konkrete Techniken zu deren Umsetzung. Weiterhin gehen wir auf wesentliche Aspekte der Gestaltung und Bewertung von Empfehlungssystemen ein und diskutieren anwenderrelevante Themen wie Usability und Vertrauen in systemgenerierte Empfehlungen.

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Notes

  1. 1.

    https://recsys.acm.org.

  2. 2.

    Ohne Beschränkung der Allgemeinheit erläutern wir das Vorgehen in diesem Abschnitt anhand von explizitem Feedback in Form von Bewertungen auf einer 5-Sterne-Skala.

  3. 3.

    https://wiki.dbpedia.org.

  4. 4.

    https://mahout.apache.org.

  5. 5.

    https://aws.amazon.com/de/personalize/.

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  1. Lehrstuhl für Interaktive Systeme und Interaktionsdesign, Universität Duisburg-Essen, Duisburg, Deutschland

    Jürgen Ziegler & Benedikt Loepp

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  1. Jürgen Ziegler
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  2. Benedikt Loepp
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Correspondence to Jürgen Ziegler or Benedikt Loepp .

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  1. Universität Duisburg-Essen, Essen, Germany

    Tobias Kollmann

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Ziegler, J., Loepp, B. (2019). Empfehlungssysteme. In: Kollmann, T. (eds) Handbuch Digitale Wirtschaft. Springer Reference Wirtschaft . Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-17345-6_52-1

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  • DOI: https://doi.org/10.1007/978-3-658-17345-6_52-1

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