ABIS 2024

Beschreibung

We invite participation in the ABIS 2024 half-day workshop on adaptivity and user modeling which is held on-site in conjunction with the MuC 2024 conference in Karlsruhe, Germany. The goals of this workshop are 1) strengthening the community of researchers (also within the German Gesellschaft für Informatik) and the HCI section for this important and emerging area of research by fostering knowledge exchange and facilitating networking, 2) providing a platform to present and discuss scientific work on recent developments relevant with respect to the topics of the workshop, and 3) discussing a research agenda for future work on personalization and adaptation approaches in these diverse fields. The workshop will be open but we invite submissions in the form of demo papers of 1-2 pages, late-breaking results papers of 2-4 pages, and full papers of 4-6 pages in length (excluding references), submitted via ConfTool until June 9th, 2024 in two-column ACM format. Papers will be peer-reviewed by at least two reviewers. In accordance with the timeline published for MuC 2024, acceptance notifications will be sent out in early July, 2024. Camera-ready versions will be due July 30th, 2024, at the latest. Accepted workshop papers will be published in the GI Digital Library. Authors of accepted full papers will be invited to orally present their work at the workshop, including discussion with the audience. In a poster and demo session (and during coffee), authors of accepted demo and late-breaking results papers will be asked to present their work. At least one author of each accepted submission must attend the workshop and must register for at least one day of the conference.

This year's edition of the ABIS workshop is planned as a half-day on-site event in conjunction with the MuC 2024 conference in Karlsruhe, Germany. The workshop will be split into two parts:
The first part of the workshop will be devoted to the presentation of scientific work addressing concepts, ongoing developments, and empirical evaluations within the thematic scope. To engage participants with the broader scope of ABIS research, we plan to have a keynote speech and possibly a panel discussion.
The second part of the workshop will focus on networking and, in particular, the discussion of a research agenda. We plan to take and classify notes for this interactive part of the workshop. Next, single topics will be discussed in smaller groups in order to characterize important elements, find main opportunities, and identify pain points for the agenda for future research, which we will put together afterward and make accessible via the workshop website

We welcome participants both from academia and industry. The target audience of the workshop are, for instance, HCI practitioners and developers, as well as researchers including (PhD) students.

The workshop welcomes a range of topics of interest, not necessarily concerned with this year's focus on personalization in CSCW-XR and making sense of sensor data for personalization purposes, including but not limited to:

• Personalization for groups: Personalized support for groups can help in our contemporary, inter-connected workplaces: Topics include adaptive ad-hoc support for meetings, suggestions of suitable collaboration partners, and similar approaches (for an overview, see [5])
• Serendipity, Bubbles, and Long Tail: Personalization is in latent danger of strictly limiting content to individual preferences, effectively, preventing the chance to find interesting items that are part of the long tail. What can be done to prevent resulting bubbles?
• Moving the Needle on the Reality/Virtuality Contiunuum: Individuals differ highly in their preferences regarding the usage of virtual and augmented reality interaction. Task requirements and the novelty of the technologies make a balanced and successful interaction challenging.
• Making Sense of Sensor Data: data is necessary for personalization but gathering explicit data, while reliable, is costly in terms of interaction time. How can we make sense of implicit (sensor) data for personalization purposes? Approaches to pattern detection, ML and the like are discussed here
• 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 application 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