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Subject: [AISWorld] ACM UMAP Workshop - HAAPIE 2021 1st CALL FOR PAPERS
Date: Wed, 17 Feb 2021 10:23:25 +0100
From: pgerman <pgerman@cs.ucy.ac.cy>
To: Aisworld <aisworld@lists.aisnet.org>, Ah <ah@listserver.tue.nl>


ACM UMAP Workshop - HAAPIE 2021 1st CALL FOR PAPERS

The 6th International Workshop on Human Aspects in Adaptive and Personalized Interactive Environments, in conjunction with the 29th ACM Conference on User Modeling, Adaptation and Personalization (ACM UMAP 2021), ONLINE from Utrecht, the Netherlands, 21-25 June 2021.

Full details are available online: http://haapie.cs.ucy.ac.cy

# IMPORTANT DATES

Submission deadline: 26 Macrh 2021
Notification: 19 April 2021
Camera-ready: 07 May 2021

# MOTIVATION & GOALS

State-of-the-art approaches in adaptation and personalization research consider user models that mostly maintain information regarding the “traditional” user characteristics (i.e., experience, knowledge, interests, context), and related contextual or technology aspects (i.e., displays, connectivity, processing power). While modeling these factors has shown significant improvements and benefits to the end-users in terms of user experience, there is an urgent need for a step change signifying the further engagement into research that will produce more holistic human-centered practices. The vision is to highlight the “human-in-the-loop” approach considering intrinsic user characteristics and abilities, like perceptual, personality, visual, cognitive and emotional factors adhering the theories of individual differences. Moreover, recent studies show the need for broadening the scope of diversity parameters to include characteristics such as motivation, self-actualization, and socio-cultural differences.
The overarching goal of HAAPIE 2021 is to bring together researchers and practitioners working in areas of human aspects in adaptation and personalization, and aims to:

- Explore state-of-the-art and new implicit and explicit methods and techniques for modeling a broad range of human factors of users and behaviors – both separately and in possible combinations (e.g., cognitive abilities and age; motivation and cultural differences);
- Explore personalization methods, computational intelligence algorithms, recommendation models, and real-time paradigms that can improve the efficiency and effectiveness of human-centered user tasks and interventions;
- Compare challenges and experiences in different real world contexts and applications (e.g., decision support, learning, wellbeing, security), where a holistic view on human aspects is needed to provide a positive user experience; and
- Identify theoretical and computational models for the design, development and evaluation of human aspects in adaptation and personalization.

The added value will be to shape new human-centered adaptive interactive environments and personalized platforms that can contribute towards viable long-term solutions.

# TOPICS OF INTEREST

Topics of interest include, but are not limited to:
- Human-centered Modeling, Adaptation Methods and Techniques
- Influence of Human Factors on Interactive Systems for Personalization
- Usage of Human Factors for Personalization
- Implicit and Explicit Detection of Human Factors for Personalization
- Human-centered Algorithms for Content Recommendation and Delivery
- Novel Human-centered Interaction Concepts and User Interfaces
- Individual Differences (Personality, Cognition, Gender, Age, etc.)
- Synergy of Affective and Human Cognitive Factors
- Modeling Groups and Communities of Diverse Users
- Evaluation of Human Aspects in Adaptation and Personalization
- Personalized Access to Services Content
- User Experience in Human-centered Systems
- Cultural and Language Diversity and Adaptation
- Age-specific Personalization and Adaptation
- Adaptation and Personalization for Users with Special Needs
- Personalization and Adaptation for Behavior Change
- User Context Awareness
- Human Aspects in Personalized Internet of Things Applications
- User-centric Cyber-Physical-Social Adaptive Systems
- Human Aspects in Social Adaptive Robots
- Adaptation and Personalization in Usable Privacy and Security
- Privacy & Ethical Aspects of Modeling Human Factors in Personalization Systems

# TYPES OF PAPERS

In HAAPIE 2021 we encourage original and relevant contributions focusing on experiences and lessons learned from real-life applications, current state-of-the-art methodologies, challenges tackled and solutions adopted, tools, algorithms, and services in the academic, public or private sector, studies, theories, techniques, and evaluation procedures that could support human-centered adaptation and personalization issues in various levels of interactive environments.
All workshop papers must contain original, previously unpublished, research work abiding the two publication types:

- Full research papers (10 pages, incl. references), proposing new approaches, innovative methods and research findings. They should make substantial theoretical and empirical contributions to the research field.
- Short research papers (7 pages, incl. references), presenting work in progress, lessons learnt, positions, emerging or future research issues and directions on human aspect challenges in the area.

Manuscripts should be formatted using the new workflow for ACM publications – as single-column paper submissions. Instructions and templates are available here: https://www.acm.org/publications/taps/word-template-workflow.

# SUBMISSION & PUBLICATION

All papers will undergo a peer review process by at least two expert reviewers to ensure a high standard of quality. Referees will consider originality, significance, technical soundness, clarity of exposition, and relevance to the workshop's topics.
Research papers should be submitted electronically as a single PDF file through the EasyChair submission system by selecting the track "Workshop-HAAPIE" (https://easychair.org/conferences/?conf=acmumap2021). Accepted papers will be published by ACM and will be available via the ACM Digital Library.

# ORGANIZING COMMITTEE

Panagiotis Germanakos, SAP SE, DE
Vania Dimitrova, University of Leeds, UK
Ben Steichen, California State Polytechnic Uni., Pomona, USA
Alicja Piotrkowicz, Scaled Insights, UK & University of Leeds, UK

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