Amra Delic
Judith Masthoff
ABSTRACT
Recommender systems for groups are becoming increasingly popular since many information needs originate from group and social activities, such as listening to music, watching movies, traveling, etc. There has been substantial progress on systems which recommend items to groups of users. However, many challenges remain. The goal of this tutorial is to introduce group recommendation and group modeling to the UMAP audience. First we will introduce the problem of making recommendations to groups and adapting to groups, and give an overview of the state-of-the art approaches to group recommendation. Next, we will also analyze more challenging topics, such as including different behavioral aspects into group modeling, and evaluation of group recommendations. Throughout, hands-on activities will be included. The tutorial will conclude with a summary of challenges and open issues.
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Digital Library
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- A. Delic, J. Masthoff, J. Neidhardt, and H. Werthner. 2018 a. How to Use Social Relationships in Group Recommenders: Empirical Evidence Proceedings of the 26rd international conference on User Modeling, Adaptation and Personalization, UMAP 2018. Singapore, Singapore. Google ScholarDigital Library
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Index Terms
- Group Recommender Systems
Recommendations
How to Use Social Relationships in Group Recommenders: Empirical Evidence
UMAP '18: Proceedings of the 26th Conference on User Modeling, Adaptation and PersonalizationIn this paper we present the results of a user study focusing on social relationships within small groups. The goal is to better understand how to incorporate the information about social relationships in group recommendation models. Our analysis, ...
Content-based group recommender systems: A general taxonomy and further improvements
Highlights- Introduction of a taxonomy for content-based group recommendation systems.
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AbstractGroup recommender systems have emerged as a solution to recommend interesting, suitable, and useful items that are consumed socially by groups of people, rather than individually. Such systems have pushed for the use of new ...
View-based recommender systems
RecSys '09: Proceedings of the third ACM conference on Recommender systemsDifferent recommender systems based on collaborative technology have been proposed that recommend new relevant products to users by exploring past user preference patterns. The most common approach generates recommendations based on user consumption ...
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