Submissions
Authors can submit their papers through Easy Chair at the link: easychair.org/conferences/?conf=umap23 using the GMAP 2023 track.
See important dates for deadlines.
TOPICS
We seek contributions in topics including, but not limited to:
Group Recommender Systems and Group Modeling.
Going beyond standard aggregation strategies, by incorporating adaptable user and group profiles as the group advances towards their choice.
How to ensure that each user's recommendation is appropriately taken into consideration when creating group recommendations?
How to adapt such recommendations to the user's changing preferences, if any?
What is the best aggregation method for user profiles?
Group decision-making process support.
How can we best help groups to reach their joint decisions, when discussion or several rounds of suggestions are supported by the system?
How to decide the appropriate time and format of the suggestion?
Adaptive team formation systems.
How to design systems and algorithms that adapt their team formation decisions to the involved users' suggestions?
How to ascertain that workers can efficiently explore the very large space of potential collaborators, and form the work alliances that are optimal for themselves but also for each (creative) task?
How to develop modeling approaches that afford users personal liberty and flexibility (e.g. in selecting their teammates), while maintaining appropriate collaboration and work conduct standards (e.g. in avoiding workplace discrimination)?
Explainability.
How can the reasoning of a Group Recommender System be made more transparent and interpretable to group members, so that the trust in a system as well as willingness to accept recommendations is increased?
How to assist online crowd workers to interpret the team formation algorithm's decisions? How to assist them comprehend the impact that their own input to the algorithm has, in the context of several decision interconnections?
Adaptability.
When a Group Recommender System serves as a decision-support tool within a conversational system, how can this system be made more adaptable to (i) group dynamics, (ii) contextual situation, (iii) moods and emotions in the group, (iv) diversity and specificity of preferences in different “sub-domains”, etc.?
Privacy.
What are the limitations of existing approaches for implementing privacy in Group Recommender Systems, and how to overcome these limitations?
What are the trade-offs that must be made between privacy and explainability?
Fairness.
What are the potential trade-offs between fairness and other performance metrics, such as accuracy and personalization? How can these trade-offs be balanced to improve the overall performance?
Evaluation.
How to tackle the lack of appropriate data sets?
How to define a “valid” set of baselines considering different dimensions and features of a Group Recommender System being evaluated?
How to define a well generalising framework that covers particularities of various Group Recommender System goals which will yield reproducible outputs?
SUBMISSION
We encourage the submission of original and novel contributions as (A) Short Papers (till 7 pages + reference - new ACM single column format) or (B) Long Papers (between 8 and 14 pages + reference - new ACM single column format);
Submission site: https://easychair.org/my/conference?conf=umap23 (select track GMAP Workshop)
All submitted papers will be evaluated by at least two members of the program committee, based on originality, significance, relevance and technical quality. The review process will be single-blind (Authors' names and affiliations can be included in the submission).
Papers must be formatted using the new ACM single-column format template. The templates and instructions are available here: https://www.acm.org/publications/taps/word-template-workflow
Available templates:
LaTeX (use \documentclass[manuscript, review, anonymous]{acmart} in the sample-authordraft.tex file for single-column): Preparing Your Article with LaTeX (acm.org)
Overleaf (use \documentclass[manuscript,review,anonymous]{acmart} for single-column): Overleaf (acm.org)
Authors are strongly encouraged to provide “alt text” (alternative text) for floats (images, tables, etc.) in their content so that readers with disabilities can be given descriptive information for these floats that are important to the work. The descriptive text will be displayed in place of a float if the float cannot be loaded. This benefits the author and it broadens the reader base for the author’s work. Moreover, the alt text provides in-depth float descriptions to search engine crawlers, which helps to properly index these floats. Additionally, authors should follow the ACM Accessibility Recommendations for Publishing in Color and SIG ACCESS guidelines on describing figures.
Note: Accepted papers will be subject to further revision to meet the requirements of the camera-ready format required by ACM. We strongly recommend the usage of LaTeX/Overleaf for the camera-ready papers to minimize the extent of reformatting. Users of the Word template must use either the version for Microsoft Word for Windows, Macintosh Office 2011, or Macintosh Office 2016 (other formats such as Open Office, etc., are not admitted) for the camera-ready submission to avoid incompatibility issues. Instructions for preparing the camera-ready versions of accepted papers will be provided after acceptance. This might include instructions to prepare a video of the accepted contribution. Camera-ready versions of accepted papers will be later submitted using ACM’s new production platform where authors will be able to review PDF and HTML output formats before publication. All accepted papers will be published by ACM within the UMAP 2023 adjunct proceedings and will be available via the ACM Digital Library. At least one author of each accepted paper must register for the workshop and present the paper there.