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GMAP 2024: 3rd Workshop on Group Modeling, Adaptation and Personalization

Published: 28 June 2024 Publication History

Abstract

While most recommender systems cater to individual users’ needs, there are numerous situations where these systems are needed to meet groups’ demands. These systems are broadly labelled as Group Recommender Systems (GRSys). Traits like interpersonal relationships, group mood, and emotional contagion are essential to fulfilling the group’s needs. However, the group’s characteristics are frequently ill-defined and dynamic and are typically absent from systems modeling. Moreover, GRSys must maneuver between the needs of the group and the individuals when opinions differ and can contradict each other. The third edition of GMAP proposes consolidating a community of scholars interested in group modeling, adaptation, and personalization. Through the workshop, researchers continue their examination of the difficulties and possibilities of creating efficient procedures and instruments to facilitate collective decision-making. GMAP 2024 offered this unique opportunity to gather scholars from different fields to enrich discussions over GRSys’ research. The workshop also allowed attendees to strengthen their networks and establish new connections conducive to cutting-edge collaborative research.

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cover image ACM Conferences
UMAP Adjunct '24: Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization
June 2024
662 pages
ISBN:9798400704666
DOI:10.1145/3631700
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 28 June 2024

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Author Tags

  1. Explainability
  2. Group Formation
  3. Group Psychology
  4. Group Recommender Systems

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Overall Acceptance Rate 162 of 633 submissions, 26%

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