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Workshop on Explainable User Models and Personalised Systems (ExUM)

Published: 04 July 2022 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 us music or movies to personal assistants able to 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. 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 the recent methodologies for building user models or developing personalized and adaptive systems.

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  • (2024)Predicting movies’ eudaimonic and hedonic scoresInformation Processing and Management: an International Journal10.1016/j.ipm.2023.10361061:2Online publication date: 12-Apr-2024

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Published In

cover image ACM Conferences
UMAP '22 Adjunct: Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization
July 2022
409 pages
ISBN:9781450392327
DOI:10.1145/3511047
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: 04 July 2022

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Author Tags

  1. Explainability
  2. Explanations
  3. Interpretability
  4. Personalization
  5. Recommender Systems
  6. Transparency
  7. User Models

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  • Extended-abstract
  • Research
  • Refereed limited

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UMAP '22
Sponsor:

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Overall Acceptance Rate 162 of 633 submissions, 26%

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UMAP '25

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Cited By

View all
  • (2024)Predicting movies’ eudaimonic and hedonic scoresInformation Processing and Management: an International Journal10.1016/j.ipm.2023.10361061:2Online publication date: 12-Apr-2024

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