Personalized HCI Book

Title of Book

Personalized Human-Computer Interaction

Current Status

The book has been published in September 2019 by De Gruyter Oldenbourg. Full details can be found here:


1. Mark P. Graus, Bruce Ferwerda: Theory-Driven User Models for Personalization
2. Sarah T. Völkel, Ramona Schödel, Daniel Buschek, Clemens Stachl, Quay Au, Bernd Bischl, Markus Bühner, Heinrich Hußmann: Opportunities and Challenges of Utilizing Personality Traits for Personalization in HCI: Towards a shared perspective from HCI and Psychology


3. Mirjam Augstein, Thomas Neumayr: Automated Personalization of Input Methods and Processes
4. Tobias Moebert, Jan Schneider, Dietmar Zoerner, Ulrike Lucke: How to use Socio-Emotional Signals for Adaptive Training
5. Dietmar Jannach, Michael Jugovac, Ingrid Nunes: Explanations and User Control in Personalized Systems


6. Daniel Herzog, Linus W. Dietz, Wolfgang Wörndl: Tourist Trip Recommendations - State of the Art and Future Challenges
7. Wilfried Grossmann, Julia Neidhardt, Hannes Werthner: Pictures as a tool for matching tourist preferences with destinations
8. Xiangdong Li, Weidong Geng: Towards Personalised Cross-objects Interface Delivery in Virtual Reality Museum Touring
9. Peter Knees, Markus Schedl, Bruce Ferwerda, Audrey Laplante: Listener Awareness in Music Recommender Systems
10. Julio Abascal, Olatz Arbelaitz, Xabier Gardeazabal, Javier Muguerza, Juan E. Pérez, Xabier Valencia, Ainhoa Yera: Personalizing the User Interface to People with Disabilities
11. Milos Kravcik: Adaptive Workplace Learning Assistance


Mirjam Augstein. University of Applied Sciences Upper Austria, Hagenberg, Austria
Eelco Herder. Radboud Universiteit Nijmegen, the Netherlands
Wolfgang Wörndl. Technische Universität München, Germany


DeGruyter Oldenbourg

Short Description

Decades of research on user modeling, personalization and recommender systems has led to a solid body of general approaches, principles, algorithms and tools. Personalization has become a core functionality in search engines, online stores and social media feeds. In the area of human-computer interaction, personalization also plays a prominent role. For instance, interaction with computer-based devices requires users to exhibit a wide range of physical and cognitive abilities. These interaction abilities might differ drastically but only few applications are reasonably accessible (i.e., usable without barriers also by people with different kinds of impairments). Further, most users, even if physically and cognitively capable of all necessary activities, have preferred interaction styles, modalities, devices and user interfaces which raises the need for individualization in all aspects of HCI. Even though personalization is a commonly adopted technology, many principles and insights from the research community have not yet sufficiently been adopted

In this book, core researchers present the state-of-the-art in research and practice on personalization from the perspective of HCI in a wide range of areas. Although personalization bears a lot of potential, it also raises additional challenges most of which are ultimately related to user acceptance (e.g., privacy issues, transparency and scrutability of data collection, data acquisition and modeling, lack of diversity and serendipity and other barriers for adoption).

Topics (not limited to)

  • Personalized interaction: approaches to personalize user input or system feedback (involving novel interaction paradigms), related prototypes and studies
  • Adaptive or intelligent user interfaces: adaptive dialogues, menus or other means of interaction, intelligent agents, feedback mechanisms, interaction with ubiquitous environments, new paradigms in human-computer interaction
  • Evaluation of personalized systems and user studies: laboratory studies, empirical studies in the field and analysis of existing corpora of usage data
  • Personalization and recommendation: applications in social networks, search, online stores, mobile computing, e-learning, automotive domain and other applications areas; interaction with recommender systems, explaining recommendations to users
  • Personalization as means of assistive technology: assisting elderly or people with impairments regarding interaction with computer-based systems
  • Obtaining user data: logging tools, aggregation of data from social networks and other Web 2.0 services, location tracking, sensor networks
  • Modeling user data: collaborative filtering, cross-application issues, contextualization and disambiguation, use of ontologies and folksonomies
  • Privacy issues, transparency, user control and scrutability
  • Adaptive support for learning and teaching: methods and tools for individual support in the knowledge acquisition process, adaptive support for collaborative learning

Review Process

There will be a two-stage review process. Submitted abstracts will be reviewed by the organization board, focusing on the suitability of the proposed chapter topic to the book. Authors of accepted abstracts will have a period of about two months to prepare their chapter (full text). The chapter will then be evaluated by at least two experts in the field, plus a meta-reviewer.

The editorial board will comprise about 15 experts actively working in the fields of Personalization, User Modeling and HCI.

Submission and Formatting

Abstracts should be submitted via EasyChair containing:

  1. Title of the proposed chapter
  2. Author(s) of the proposed chapter (including affiliation)
  3. Abstract of max. 500 words describing contents of the book chapter
  4. Keywords (at least 2, no more than 5)

Chapters should be submitted via EasyChair containing:

  1. Title of the proposed chapter
  2. Author(s) of the proposed chapter (including affiliation)
  3. Abstract of max. 500 words describing contents of the book chapter
  4. Keywords (at least 2, no more than 5)
  5. Manuscript (maximum of 8000 words, each Figure or Table counting as 200 words)

Full book chapters need to be formatted according to the DeGruyter Oldenbourg instructions in Word or PDF format:

Please submit your chapters via EasyChair:

Team of Reviewers

Luca Aiello, Nokia, United Kingdom
Liliana Ardissono, University of Torino, Italy
Mirjam Augstein, University of Applied Sciences Upper Austria
Matt Dennis, University of Portsmouth, United Kingdom
Bruce Ferwerda, Jönköping University, Sweden
Angela Fessl, Know-Center, Graz, Austria
Panagiotis Germanakos, SAP SE & University of Cyprus
Eelco Herder, Radboud University, the Netherlands
Daniel Herzog, Technical Unviersity of Munich, Germany
Dietmar Jannach, Alpen-Adria Universität Klagenfurt, Austria
Milos Kravcik, RWTH Aachen, Germany
Ralf Krestel, Hasso Plattner Institute & University of Potsdam, Germany
Ulrike Lucke, University of Potsdam, Germany
Cataldo Musto, University of Bari “Aldo Moro”, Italy
Julia Neidhardt, Vienna University of Technology, Austria
Alexandros Paramythis, Contexity AG, Switzerland
Olga Santos, aDeNu Research group (UNED), Spain
Sergey Sosnovsky, Utrecht University, the Netherlands
Natasha Stash, Eindhoven University of Technology, the Netherlands
Marko Tkalcic, Free University of Bozen-Bolzano, Italy
Carsten Ullrich, DFKI – German Center for Artificial Intelligence
Arjen de Vries, Radboud University, the Netherlands
Stephan Weibelzahl, Private University of Applied Sciences Goettingen, Germany
Wolfgang Wörndl, Technical University of Munich, Germany
Sergej Zerr, L3S Research Center, Germany