Algorithms for Group Recommendation

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Abstract

In this chapter, our aim is to show how group recommendation can be implemented on the basis of recommendation paradigms for individual users. Specifically, we focus on collaborative filtering, content-based filtering, constraint-based, critiquing-based, and hybrid recommendation. Throughout this chapter, we differentiate between (1) aggregated predictions and (2) aggregated models as basic strategies for aggregating the preferences of individual group members.
Originalspracheenglisch
TitelGroup Recommender Systems
UntertitelAn Introduction
ErscheinungsortCham
Herausgeber (Verlag)Springer
Kapitel2
Seiten27-58
Seitenumfang32
ISBN (elektronisch)978-3-319-75067-5
ISBN (Print)978-3-319-75066-8
DOIs
PublikationsstatusVeröffentlicht - 2018

Publikationsreihe

NameSpringerBriefs in Electrical and Computer Engineering

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    Felfernig, A., Atas, M., Helic, D., Tran, T. N. T., Stettinger, M., & Samer, R. (2018). Algorithms for Group Recommendation. in Group Recommender Systems: An Introduction (S. 27-58). (SpringerBriefs in Electrical and Computer Engineering). Cham: Springer. https://doi.org/10.1007/978-3-319-75067-5_2