tutorial

Tutorial on Offline Evaluation for Group Recommender Systems

Authors:

Francesco Barile,

Ladislav PeskaAuthors Info & Claims

RecSys '22: Proceedings of the 16th ACM Conference on Recommender Systems

Pages 702 - 705

https://doi.org/10.1145/3523227.3547371

Published: 13 September 2022 Publication History

Abstract

Group Recommender Systems (GRSs), unlike recommendations for individuals, provide suggestions for groups of people. Clearly, many activities are often experienced by a group rather than an individual (visiting a restaurant, traveling, watching a movie, etc.) hence the requirement for such systems. The topic is gradually receiving more and more attention, with an increased number of papers published at significant venues, which is enabled by the predominance of online social platforms that allow their users to interact in groups, as well as to plan group activities. However, the research area lacks certain ground rules, such as basic evaluation agreements. We believe this is one of the main obstacles to make advances in the research area, and to enable researchers to compare and continue each others’ works. In other words, setting the basic evaluation agreements is a stepping-stone towards reproducible Group Recommenders research. The goal of this tutorial is to tackle this problem, by providing the basic principles of the GRSs offline evaluation approaches.

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Cited By

Barile FDelić APeska LSaccardi IVinella FBoratto LGena CMarras MGermanakos PPopescus E(2024)GMAP 2024: 3rd Workshop on Group Modeling, Adaptation and PersonalizationAdjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization10.1145/3631700.3658535(316-318)Online publication date: 27-Jun-2024
https://dl.acm.org/doi/10.1145/3631700.3658535

Index Terms

Tutorial on Offline Evaluation for Group Recommender Systems
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
  2. Information systems applications

Index terms have been assigned to the content through auto-classification.

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RecSys '22: Proceedings of the 16th ACM Conference on Recommender Systems

September 2022

743 pages

ISBN:9781450392785

DOI:10.1145/3523227

Copyright © 2022 ACM.

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Published: 13 September 2022

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RecSys '22: Sixteenth ACM Conference on Recommender Systems

September 18 - 23, 2022

WA, Seattle, USA

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Overall Acceptance Rate 254 of 1,295 submissions, 20%

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Cited By

Barile FDelić APeska LSaccardi IVinella FBoratto LGena CMarras MGermanakos PPopescus E(2024)GMAP 2024: 3rd Workshop on Group Modeling, Adaptation and PersonalizationAdjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization10.1145/3631700.3658535(316-318)Online publication date: 27-Jun-2024
https://dl.acm.org/doi/10.1145/3631700.3658535

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