User Modeling and User-Adapted Interaction
Special Issue on "Group Recommender Systems"

Aims and Scope

Group Recommender Systems determine recommendations for groups. These systems often apply basic recommendation strategies and try to aggregate the results in such a way, that recommendations become acceptable for all or most of the group members.

However, there are still plenty of open issues to be solved especially due to the nature of group decision scenarios. In contrast to single user recommender systems, recommender systems for groups must take into account aspects such as group dynamics, emotions, personality, heterogeneity of groups, and group types (e.g., homogeneous vs. inhomogeneous groups). These factors make recommender-based decision support a challenge with a multitude of related research questions also including psychological aspects, for example, "How to best take into account models of human decision making in group-based recommendation scenarios?"

Moreover, group settings are becoming prominent in a variety of scenarios, such as conversational systems, which could help exploiting the interaction between group members, and algorithmic fairness, where groups play a key role to assess possible forms of discrimination in the recommendation process. In addition to this, the relation of group recommendation with respect to recent regulations, such as GDPR, which require algorithms to be explainable, privacy-preserving, and unbiased, opens a plethora of relevant issues to tackle in the group recommendation research.

Researchers from both academia and industry are invited to submit original and excellent research results on topics related to group recommendation, from algorithms to applications.

Special Issue Topics

We are interested in contributions focusing on different new and relevant aspects of group recommender systems, in particular, new developments on the algorithmic and user interface level as well as new applications, all accompanied by a corresponding evaluation (e.g., empirical study) that clearly shows significant improvements compared to the state of the art.

The general topics regarded as relevant for the special issue on "Group Recommender Systems"' include but are not limited to

  • User modeling:
    • User modeling aspects in group recommendation scenarios
    • Individual preferences' refinement approaches
    • User trust and reputation in the context of a group
  • Group modeling:
    • New approaches to preference aggregation
    • Modeling user-to-user and user-to-system interactions
    • Modeling dependency dynamics
    • Psychological modeling of group recommendation tasks
  • Algorithmic and application perspectives:
    • New algorithms for group recommender systems
    • User interfaces for group recommender systems
    • Conversational approaches in group recommender systems, conveying both multi- and single-turn conversations
    • Privacy-preserving group recommender systems
    • New approaches to explain recommendations for groups
    • Group recommendation approaches beyond basic items (e.g., sequences and packages)
    • Approaches to multi-stakeholder recommendation
    • Interplay between individual and group recommender systems (e.g., how individual recommender can benefit from group ones)
    • Novel functionalities and interface for choice support in the group decision-making
    • Applications of group recommender systems
  • Evaluation:
    • New approaches to preference acquisition and aggregation
    • Novel evaluation methods for group recommender systems
    • Documented datasets for group recommendation scenarios (including baseline results)
  • Social and societal perspectives:
    • Social factors in group recommender systems
    • Group dynamics for group recommender systems
    • Addressing societal and beyond-accuracy perspectives in group recommender systems (e.g., data and algorithmic bias and fairness)
    • Approaches to group formation in the context of group recommendation
    • Negotiation mechanisms for group recommender systems
    • Cultural aspects of group recommender systems
    • Transparency in group recommender systems

Important Dates

  • Abstract submission: October 15, 2021
  • Abstract notification: November 15, 2021
  • Paper submission: February 15, 2022
  • Author notification: April 15, 2022
  • Revised paper submission: June 15, 2022
  • Final notification: July 30, 2022
  • Camera-ready paper submission: September 2, 2022

All deadlines are 11:59pm, AoE time (Anywhere on Earth).

Submission Details

All submissions must be written in English. We expect authors, reviewers, and the organizing committee to adhere to the ACM’s Conflict of Interest Policy and the ACM’s Code of Ethics and Professional Conduct. Authors should use follow the journal's submission instructions.

Authors must submit an extended abstract via EasyChair by the deadline indicated above. It must be at most 3 pages long, not counting references, and formatted according to the journal template. The guest editors of the special issue will then screen all submitted extended abstracts and will invite authors of submissions that pass this screening to submit a full manuscript to be submitted via the journal’s submission system. Abstracts should be submitted as PDF files to Easychair at https://easychair.org/conferences/?conf=umuaigrouprecsys21.

After abtracts have been accepted, the final full submission needs to be done through the UMUAI journal submission system.

Committee

Guest Editors

Contacts

For general enquiries on the workshop, please send an email to ludovico.boratto@acm.org, afelfern@ist.tugraz.at, martin.stettinger@ist.tugraz.at, and marko.tkalcic@gmail.com.