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extended-abstract

5th Workshop on Explainable User Models and Personalised Systems (ExUM)

Published: 16 June 2023 Publication History

Abstract

Adaptive and personalized systems have become pervasive technologies, gradually playing an increasingly important role in our daily lives. Indeed, we are now used to interacting with algorithms that help us in several scenarios, ranging from services that suggest music or movies to personal assistants who proactively support us in complex decision-making tasks. As the importance of such technologies in our everyday lives grows, it is fundamental that the internal mechanisms that guide these algorithms are as clear as possible. It is not by chance that the EU General Data Protection Regulation (GDPR) emphasized the users’ right to explanation when people face intelligent systems. Unfortunately, current research tends to go in the opposite direction since most of the approaches try to maximize the effectiveness of the personalization strategy (e.g., recommendation accuracy) at the expense of model explainability. The workshop aims to provide a forum for discussing problems, challenges, and innovative research approaches in this area by investigating the role of transparency and explainability in recent methodologies for building user models or developing personalized and adaptive systems.

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cover image ACM Conferences
UMAP '23 Adjunct: Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization
June 2023
446 pages
ISBN:9781450398916
DOI:10.1145/3563359
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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 June 2023

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Author Tags

  1. Explainability
  2. Interpretability
  3. Personalization
  4. Recommender Systems
  5. Transparency
  6. User Modeling

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  • Extended-abstract
  • Research
  • Refereed limited

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UMAP '23
Sponsor:

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Overall Acceptance Rate 162 of 633 submissions, 26%

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UMAP '25

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