-------- Forwarded Message --------
*** First Call for Papers ***
UMAP ’23: 31st ACM Conference on User Modeling, Adaptation and
Personalization
June 26 - 29, 2023, St. Raphael Resort, Limassol, Cyprus
https://www.um.org/umap2023/
ACM UMAP is the premier international conference for researchers
and practitioners
working on systems that adapt to individual users or groups of
users, and that
collect, represent, and model user information. ACM UMAP is
sponsored by ACM SIGCHI and SIGWEB. User Modeling Inc., as the
core Steering Committee, oversees
the conference organization. The proceedings, published by ACM,
will be part of the
ACM Digital Library.
The theme of UMAP 2023 is "Personalization in Times of Crisis”.
Specifically, we welcome submissions that highlight the impact
that critical periods (such as the COVID-19 pandemic, ongoing
wars, and climate change, to name a few) can have on
user modeling, personalization, and adaptation of (intelligent)
systems; the focus is on investigations that capture how these
trying times may have influenced user behavior and whether new
models are required.
While we encourage submissions related to this theme, the scope of
the conference
is not limited to the theme only. As always, contributions from
academia, industry, and other organizations discussing open
challenges or novel research approaches
are expected to be supported by rigorous evidence appropriate to
the claims (e.g., user study, system evaluation, computational
analysis).
Important Dates
• Paper Abstracts: January 19, 2023 (mandatory)
• Full paper: January 26, 2023
• Notification: April 11, 2023
• Camera-ready: May 2, 2023
• Conference: June 26 - 29, 2023
Note: The submissions deadlines are at 11:59 pm AoE time (Anywhere
on Earth)
Conference Topics
We welcome submissions related to user modeling, personalization,
and adaptation
of (intelligent) systems targeting a broad range of users and
domains. For detailed descriptions and the suggested topics for
each track please visit the UMAP 2023 website.
Personalized Recommender Systems
This track invites works from researchers and practitioners on
recommender
systems. In addition to mature research works addressing technical
aspects of recommendations, we welcome research contributions that
address questions
related to user perception, decision-making, and the business
value of
recommender systems.
Knowledge Graphs, Semantics, Social and Adaptive Web
This track welcomes works focused on the use of knowledge
representations (i.e.,
novel knowledge bases), graph algorithms (i.e., graph embedding
techniques), and social network analysis at the service of
addressing all aspects of personalization,
user model building, and personal experience in online social
systems. Moreover,
this track invites works in adaptive hypermedia, as well as
semantic and social web.
Intelligent User Interfaces
This track invites works exploring how to make the interaction
between computers
and people smarter and more productive, leveraging solutions from
human-computer
interaction, data mining, natural language processing, information
visualization, and
knowledge representation and reasoning.
Personalizing Learning Experiences through User Modeling
This track invites researchers, developers, and practitioners from
various disciplines
to submit their innovative learning solutions, share acquired
experiences, and discuss
their modeling challenges for personalized adaptive learning.
Responsibility, Compliance, and Ethics
Researchers, developers, and practitioners have a social
responsibility to account for
the impact that technologies have on individuals (users,
providers, and other stakeholders) and society. This track invites
works related to the science of building, maintaining, evaluating,
and studying adaptive systems that are fair, transparent,
respectful of users’ privacy, and beneficial to society.
Personalization for Persuasive and Behavior Change Systems
This track invites submissions focused on personalization and
tailoring for persuasive
technologies, including but not limited to personalization models,
user models, computational personalization, design, and evaluation
methods. It also welcomes work that brings attention to the user
experience and designing personalized and adaptive behavior change
technologies.
Virtual Assistants, Conversational Interactions, and Personalized
Human-robot Interaction
This track invites works investigating new models and techniques
for adapting synthetic companions (e.g., virtual assistants,
chatbots, social robots) to individual users. With the
conversational modality so in vogue across disciplines, this track
welcomes work highlighting the model and deployment of synthetic
companions driven by conversational search and recommendation
paradigms.
Research Methods and Reproducibility
This track invites submissions on methodologies to evaluate
personalized systems, benchmarks, and measurement scales, with
particular attention to the reproducibility of results and
techniques. Furthermore, the track looks for submissions that
report new insights from reproducing existing works.
Submission and Review Process
Submissions for any of the aforementioned tracks should have a
maximum length of *14 pages* (excluding references) in the ACM new
single-column format
(
https://www.acm.org/publications/proceedings-template). (Papers
of any length up
to 14 pages are encouraged; reviewers will comment on whether the
size is appropriate for the contribution.) Additional review
criteria and submission link will be available shortly on the
conference website:
https://www.um.org/umap2023/ .
Accepted papers will be included in the conference proceedings and
presented at the
conference. At least one author should register for the conference
by the early registration date cut-off.
UMAP uses a *double-blind* review process. Authors must omit their
names and affiliations from their submissions; they should also
avoid obvious identifying statements. For instance, citations to
the authors' prior work should be in the third person. Submissions
not abiding by anonymity requirements will be desk rejected.
UMAP has a *no dual submission* policy, which is why full paper
submissions should
not be currently under review at another publication venue.
Further, UMAP operates under the ACM Conference Code of Conduct
(
https://www.acm.org/about-acm/policy-against-harassment).
Program Chairs
• Julia Neidhardt, TU Wien, Austria
• Sole Pera, TU Delft, The Netherlands
Track Chairs
Personalized Recommender Systems
• Noemi Mauro (University of Torino, Italy)
• Olfa Nasraoui (University of Louisville, USA)
• Marko Tkalcic (University of Primorska, Slovenia)
Knowledge Graphs, Semantics, Social and Adaptive Web
• Daniela Godoy (ISISTAN - CONICET/UNICEN University, Argentina)
• Cataldo Musto (University of Bari, Italy)
Intelligent User Interfaces
• Bart Knijnenburg (Clemson University, USA)
• Katrien Verbert (KU Leuven, Belgium)
• Wolfgang Wörndl (TU Munich, Germany)
Personalizing Learning Experiences through User Modeling
Oleksandra Poquet (TU Munich, Germany)
• Olga C. Santos (UNED, Spain)
Responsibility, Compliance, and Ethics
• Michael Ekstrand (Boise State University, USA)
• Peter Knees (TU Wien, Austria)
Personalization for Persuasive and Behavior Change Systems
• Federica Cena (University of Torino, Italy)
• Rita Orji (Dalhousie University, Canada)
• Jun Zhao (Oxford University, England)
Virtual Assistants, Conversational Interactions, and Personalized
Human-robot Interaction
• Li Chen (Hong Kong Baptist University, Hong Kong)
• Yi Zhang (University of California Santa Cruz, USA)
• Ingrid Zukerman (Monash University, Australia)
Research Methods and Reproducibility
• Dietmar Jannach (University of Klagenfurt, Austria)
• Alan Said (University of Gothenburg, Sweden)
Contact information:
umap2023-program@um.org
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