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    UMAP 2023 - UMAP ’23: 31st ACM Conference on User Modeling, Adaptation and Personalization: Call for Papers

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    Website https://www.um.org/umap2023/ | Want to Edit it Edit Freely

    Category User Modeling; User Adaptation; User Personalisation

    Deadline: January 19, 2023 | Date: June 26, 2023-June 29, 2023

    Venue/Country: St. Raphael Resort, Limassol, Cyprus

    Updated: 2022-10-31 19:57:21 (GMT+9)

    Call For Papers - CFP

    *** 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-programatum.org


    Keywords: Accepted papers list. Acceptance Rate. EI Compendex. Engineering Index. ISTP index. ISI index. Impact Factor.
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