Research Topic

Article Collection on Human Aspects in Adaptive and Personalized Interactive Environments (HAAPIE)

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About this Research Topic

In Memory of Professor George Samaras.

Rapid technological advancement and increasing availability of big data have enabled the creation of dynamic communication environments that present highly complex and uncertain information flows, unfamiliar scenarios, situation-specific use cases and ...

In Memory of Professor George Samaras.

Rapid technological advancement and increasing availability of big data have enabled the creation of dynamic communication environments that present highly complex and uncertain information flows, unfamiliar scenarios, situation-specific use cases and multi-purpose interactions. These intelligent technologies are at the core of innovative adaptation and personalization.

A vast body of research addresses adaptation and personalization based on “traditional” user characteristics (e.g., role, experience, knowledge, interests) or related contextual aspects (e.g., displays, connectivity, processing power). While modeling these factors has shown significant improvement for personalizing the user experience, there is an urgent need for a step change in our understanding of individual differences that takes into account human aspects inclusively. This is especially relevant for systems that promote learning and behavior change as this requires more holistic human-centered adaptation and personalization.

This Research Topic is inspired by the series of HAAPIE Workshops (http://haapie.cs.ucy.ac.cy) which address the following objectives:
- to explore state-of-the-art and new implicit and explicit methods and techniques for modeling a broad range of human factors in users and behaviors – both separately and in possible combinations (e.g., cognitive abilities and age; motivation and cultural differences);
- to explore personalization techniques, computational intelligence algorithms, recommendation models, and real-time paradigms that can improve the efficiency and effectiveness of human-centered user tasks and interventions;
- to compare challenges and experience 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 promote behavior change;
- to identify theoretical and computational models for the design, development and evaluation of human aspects in adaptation and personalization.

The Research Topic encloses a selection of extended high-quality papers that have been presented in the series of HAAPIE workshops and it also draws attention to original unpublished research that has a considerable contribution and influence in the field.

Topics of interest may include:
- AI Techniques for Human-centered User Modeling and Adaptation
- Methods for Implicit and Explicit Detection of Human Factors
- Human-centered Intelligent Algorithms for Content Recommendation and Delivery
- Computational Intelligence and Human Behavior Modeling for Personalization
- Novel Human-centered Interaction Concepts and User Interfaces
- Explanation and justification in personalization systems
- Modeling Groups and Communities of Diverse Users
- Evaluation of Human Aspects in Adaptation and Personalization
- Adaptation and Personalization for Users with Special Needs
- Personalization and Adaptation for Behavior Change
- User-centric Cyber-Physical-Social Adaptive Systems
- Diversity-aware interaction systems
- Human Aspects in Social Adaptive Robots
- Adaptation and Personalization in Usable Privacy and Security


Keywords: Adaptation, Personalization, User Modeling, Human Factors, Algorithms, Computational Intelligence, User Experience, Usability, Evaluation, Human-centered Interactions, Human-Computer Interaction, Design, Tools


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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