Widening the Role of Group Recommender Systems with CAJO

Group Recommender Systems (GRSs) have been studied and developed for more than twenty years. However, their application and usage has not grown. They can even be labeled as failures, if compared to the very successful and common recommender systems (RSs) used on all the major ecommerce and social platforms. As a result, the RSs that we all use now, are only targeted for individual users, aiming at choosing an item exclusively for themselves; no choice support is provided to groups trying to select a service, a product, an experience, a person, serving equally well all the group members. In this opinion article we discuss why the success of group recommender systems is lagging and we propose a research program unfolding on the analysis and development of new forms of collaboration between humans and intelligent systems. We define a set of roles, named CAJO, that GRSs should play in order to become more useful tools for group decision making.

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Publication Details

Journal
ACM SIGIR Forum
Published
2025-06-01
DOI
https://doi.org/10.1145/3769733.3769745
Citations
2
Primary Topic
Simulation Techniques and Applications
Type
article
Field-Weighted Citation Impact
4.21
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article

Widening the Role of Group Recommender Systems with CAJO

2 citations
ACM SIGIR Forum
Simulation Techniques and Applications
4.21
article

Widening the Role of Group Recommender Systems with CAJO

article en
2 citations

Abstract

Group Recommender Systems (GRSs) have been studied and developed for more than twenty years. However, their application and usage has not grown. They can even be labeled as failures, if compared to the very successful and common recommender systems (RSs) used on all the major ecommerce and social platforms. As a result, the RSs that we all use now, are only targeted for individual users, aiming at choosing an item exclusively for themselves; no choice support is provided to groups trying to select a service, a product, an experience, a person, serving equally well all the group members. In this opinion article we discuss why the success of group recommender systems is lagging and we propose a research program unfolding on the analysis and development of new forms of collaboration between humans and intelligent systems. We define a set of roles, named CAJO, that GRSs should play in order to become more useful tools for group decision making.

ACM SIGIR ForumVol. 59(1)
University of Sarajevo (BA), Free University of Bozen-Bolzano (IT)
Peace, Justice and strong institutions
Openalex Percentile: Top 5%
Simulation Techniques and Applications
4.21
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