ABIS 2019 – 23rd International Workshop on Personalization and Recommendation on the Web and Beyond
ABIS 2019 is an international workshop, organized by the SIG on Adaptivity and User Modeling of the German Gesellschaft für Informatik. For more than 20 years, the ABIS Workshop has been a highly interactive forum for discussing the state of the art in personalization and user modeling. Latest developments in industry and research are presented in plenary sessions, forums, and tutorials. Researchers, Ph.D. students and Web professionals obtain and exchange novel ideas, expertise and feedback on ongoing research before submitting their work to major conferences such as CHI, UMAP, WWW and SIGIR.
This year, we hold the ABIS workshop at ACM Hypertext (September 17th, 2019 – Hof, Germany).
User modeling and adaptive systems deal with creating and maintaining a user model with the aim to adapt interactive systems. User models can be inferred from implicitly observed user behavior or explicitly entered information, such as the user’s profile data, the user’s current location or items that the user browsed, searched, tagged or bought earlier. Applications of personalization include recommendations of items, location-based services, updates on friend activities, interest-based portal sites, educative games and personalized guidance or help.
With the ongoing transition from desktop computers to mobile devices and ubiquitous environments, the need for more and better user modeling and personalization to adapt to changing contexts in various situations is even more important. But this also poses new challenges, including privacy problems and questions of user control. Systems may draw wrong conclusions about a user’s search actions, limit functionality due to badly designed personalized menus, or may inadvertently disclose sensitive information to colleagues and friends. In addition, the user experience is becoming more important in a mobile and connected world. It may not be only important to deliver the absolute best recommendations, but have fast and “good enough” recommendations. On the one hand, there is a battle for the attention of users. On the other hand, the cost of wrong adaptation is very high, users may quickly switch to different applications and service, if he or she is getting annoyed.
Personalization does not need to be limited to generating lists of recommendations: adaptations such as personalized maps, tailored menus, link annotation and scripting potentially have a greater effect on the user experience. A particular design issue is the explanation of why items are recommended, or which interface elements have been adapted – and how this can be made undone, if needed. And how can one encourage users to inspect and adjust their user profiles, collected information and privacy settings?
Topics include but are not limited to:
- 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
- Personalization and recommendation: applications in social networks, search, online stores, mobile computing, e-learning, automotive domain, assisting elderly or handicapped persons and other applications areas
- Privacy issues, transparency, user control and scrutability
- 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 interactions
- Personalized interaction: approaches to personalize user input or system feedback (involving novel interaction paradigms), related prototypes and studies
- Adaptive support for learning and teaching: methods and tools for individual support in the knowledge acquisition process, adaptive support for collaborative learning
- Evaluation and user studies: laboratory studies, empirical studies in the field and analysis of existing corpora of usage data
The ABIS workshop will accept the following submission types:
- Full papers (6 pages) representing mature work with a proper evaluation
- Short papers and demos (3 pages) representing work in progress and early promising results
- Vision and position papers (2 pages) providing future directions; visions may be bold, but should be backed up with relevant literature
- Abstract of journal paper or book chapter (1 page) giving an opportunity to present a published paper or chapter at this workshop as well
In addition to regular workshop submissions, we specifically aim to invite Master and Ph.D. students to submit their research plans and to present their work to the community.
- Doctoral consortium papers (2-3 pages) present preliminary results or insights, plus concrete open research questions and planned future work
- Thesis abstracts (1 page) are summaries of recently submitted Bachelor, Master or Ph.D. theses, including a (permanent) link to the paper download
We are in the process of finalizing our book on Personalized HCI, chapter authors are invited to present their work at the workshop as well.
Papers should be formatted according to the ACM Master Article Template format.
Submissions are accepted via Easychair.
- Submissions: 21.06.2019 (Deadline Extension)
- Notification: 05.07.2019
- Camera-Ready: 12.07.2019
- Workshop day: 17.09.2019 (Hof, Germany)
- Unexpected and Unpredictable: Factors That Make Personalized Advertisements Creepy (Eelco Herder, Boping Zhang)
- Descriptive Network Modeling and Analysis for Investigating User Acceptance in a Learning Management System Context (Parisa Shayan, Roberto Rondinelli, Menno van Zaanen, Martin Atzmueller)
- Behavioral Analysis on Socio-Spatial Interaction Networks Concerning User Preferences, Interactions and their Perception (Martin Atzmueller, Cicek Güven, Spyroula Masiala, Parisa Shayan, Werner Liebregts)
- Towards Requirements for Intelligent Mentoring Systems (Milos Kravcik, Katharina Schmid, Christoph Igel)
- Data-Driven Recommendations in a Public Service (Alessandro Piscopo, Maria Panteli, Douglas Penna)
- Modeling Physiological Conditions for Proactive Tourist Recommendations (Rinita Roy, Linus W. Dietz )
Book Chapter Abstract:
- Personalizing the User Interface for People with Disabilities (Julio Abascal, Olatz Arbelaitz, Xabier Gardeazabal, Javier Muguerza, Juan Eduardo Pérez, Ainhoa Yera, Xabier Valencia)
- Explanations and User Control in Recommender Systems (Dietmar Jannach, Michael Jugovac, Ingrid Nunes)
- Adaptive Workplace Learning Assistance (Milos Kravcik)
- Mirjam Augstein (University of Applied Sciences Upper Austria, Hagenberg)
- Eelco Herder (Radboud University)
- Wolfgang Wörndl (Technical University of Munich)
- Enes Yigitbas (Universität Paderborn)
- Maria Bielikova, Slovak University of Technology in Bratislava, Slovakia
- Dominikus Heckmann, Technische Hochschule Amberg-Weiden
- Dietmar Jannach, University of Klagenfurt
- Birgitta König-Ries, Friedrich Schiller University of Jena
- Felicitas Löffler, Friedrich Schiller University of Jena
- Ernesto William De Luca, Georg-Eckert-Institut
- Alexandros Paramythis, Contexity AG
- Stephan Weibelzahl, Private University of Applied Sciences Göttingen
Fachgruppe Adaptivität und Benutzermodellierung in interaktiven Softwaresystemen