Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/3386392acmconferencesBook PagePublication PagesumapConference Proceedingsconference-collections
UMAP '20 Adjunct: Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization
ACM2020 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
UMAP '20: 28th ACM Conference on User Modeling, Adaptation and Personalization Genoa Italy July 14 - 17, 2020
ISBN:
978-1-4503-7950-2
Published:
13 July 2020
Sponsors:
Next Conference
June 16 - 19, 2025
New York City , NY , USA
Bibliometrics
Skip Abstract Section
Abstract

Welcome to the 28th and the first virtual ACM International Conference on User Modeling, Adaptation, and Personalization (UMAP 2020), virtually in Genoa, Italy, July 12-18, 2020. This year, UMAP is being held virtually due to Covid-19 pandemic. In order to enable virtual participation from all time zones, every session is repeated twice, with live interaction.

UMAP is the premier international conference for researchers and practitioners working on systems that adapt to individual users or to groups of users. UMAP is the successor of the biennial User Modeling (UM) and Adaptive Hypermedia and Adaptive Web-based Systems (AH) conferences that were merged in 2009. It has traditionally been organized under the auspices of User Modeling Inc. and since 2016 UMAP is an ACM conference, sponsored by ACM SIG CHI and SIG WEB. The conference spans a wide scope of topics related to user modeling, adaptation, and personalization. As previous conferences, UMAP 2020 is focused on bringing together cutting-edge research from user interaction and modeling, adaptive technologies, and delivery platforms. It includes high-quality peer-reviewed papers featuring substantive new research in one of five main research areas:

  • User Modeling for Recommender Systems

  • Adaptive & Personalized Educational Systems

  • Intelligent User Interfaces

  • User modeling in health and safety

  • Responsible personalization (UMAP 2020 theme)

  • Personality, cognitive aspects and emotions in user modeling

This year, we received 139 long paper and 62 short paper submissions. In keeping with UMAPs rigorous standards, each paper was carefully reviewed by members of the Program Committee (PC). The international Program Committee (PC) consisted of 28 senior members who were assisted by 118 committee members. These were leading researchers as well as highly promising young researchers. Papers were assigned to at least 3 members of the PC and to 1 senior member based on their expertise, interests, and other factors. Each paper received at least 3 reviews. After the initial reviews were submitted, the designated senior PC member facilitated discussion amongst reviewers in order to resolve differences and correct misunderstandings. The senior PC member then provided a summative meta-review and a recommendation to the Program Chairs. The final decisions were based on these recommendations, the meta-reviews, and reviewer scores.

We accepted 31 (22%) of the long papers and 15 (24%) of the short paper submissions for oral presentation and inclusion in the proceedings. The program also features posters, demos, and late breaking results, which collectively showcase the wide spectrum of novel ideas and latest results in user modeling, adaptation and personalization, 29 submissions received, 19 were accepted (66%).

SESSION: Session 5: Fairness in User Modeling, Adaptation and Personalization (FairUMAP 2020)
research-article
How YouTube Leads Privacy-Seeking Users Away from Reliable Information

Online media is increasingly selected and filtered by recommendation engines. YouTube is one of the most significant sources of socially-generated information, and as such its recommendation policies are important to understand. Because of YouTube's ...

research-article
Emotion-based Stereotypes in Image Analysis Services

Vision-based cognitive services (CogS) have become crucial in a wide range of applications, from real-time security and social networks to smartphone applications. Many services focus on analyzing people images. When it comes to facial analysis, these ...

research-article
Public Access
Fair Inputs and Fair Outputs: The Incompatibility of Fairness in Privacy and Accuracy

Fairness concerns about algorithmic decision-making systems have been mainly focused on the outputs (e.g., the accuracy of a classifier across individuals or groups). However, one may additionally be concerned with fairness in the inputs. In this paper, ...

research-article
Mitigating Demographic Bias in AI-based Resume Filtering

With increasing diversity in the labor market as well as the work force, employers receive resumes from an increasingly diverse population. However, studies and field experiments have confirmed the presence of bias in the labor market based on gender, ...

research-article
Designing Recommender Systems for the Common Good

The growing inclusion of information and communication technologies in our everyday life sets the scene for the development of personalized public services. Their public character brings along challenges that have not necessarily been dealt with in ...

Contributors
  • University of Haifa
  • University of Genoa
  • University of Colorado Boulder
  • University of Turin

Recommendations

Acceptance Rates

Overall Acceptance Rate 162 of 633 submissions, 26%
YearSubmittedAcceptedRate
UMAP '191223025%
UMAP'19 Adjunct1223025%
UMAP '18932628%
UMAP '18932628%
UMAP '17802936%
UMAP '161232117%
Overall63316226%