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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 18px; color: #000000;"><b>*** Preliminary Call for Papers ***</b></span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 18px; color: #000000;">UMAP ’23: 31st ACM Conference on User Modeling, Adaptation and Personalization</span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 18px; color: #000000;">June 26 - 29, 2023, St. Raphael Resort, Limassol, Cyprus</span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 18px; color: #000000;"><a href="https://www.um.org/umap2023/ ">https://www.um.org/umap2023/ </a></span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">ACM UMAP is the premier international conference for researchers and practitioners</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">working on systems that adapt to individual users or groups of users, and that</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">collect, represent, and model user information. ACM UMAP is sponsored by ACM </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">SIGCHI and SIGWEB. User Modeling Inc., as the core Steering Committee, oversees</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">the conference organization. The proceedings, published by ACM, will be part of the</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">ACM Digital Library.</span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">The theme of UMAP 2023 is "</span><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"><b>Personalization in Times of Crisis</b></span><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">”. Specifically, we </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">welcome submissions that highlight the impact that critical periods (such as the </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">COVID-19 pandemic, ongoing wars, and climate change, to name a few) can have on</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">user modeling, personalization, and adaptation of (intelligent) systems; the focus is </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">on investigations that capture how these trying times may have influenced user </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">behavior and whether new models are required. </span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">While we encourage submissions related to this theme, the scope of the conference</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">is not limited to the theme only. As always, contributions from academia, industry, </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">and other organizations discussing open challenges or novel research approaches</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">are expected to be supported by rigorous evidence appropriate to the claims (e.g., </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">user study, system evaluation, computational analysis).</span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 18px; color: #000000;"><b>Important Dates</b></span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">•</span><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"> Paper Abstracts: January 19, 2023 (mandatory)</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">•</span><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"> Full paper: January 26, 2023</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">•</span><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"> Notification: April 11, 2023</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">•</span><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"> Camera-ready: May 2, 2023</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">•</span><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"> Conference: June 26 - 29, 2023</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">Note: The submissions deadlines are at 11:59 pm AoE time (Anywhere on Earth)</span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 18px; color: #000000;"><b>Conference Topics</b></span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">We welcome submissions related to user modeling, personalization, and adaptation</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">of (intelligent) systems targeting a broad range of users and domains. Detailed </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">descriptions and the suggested topics for each track will be available shortly in the </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">extended version of the CFP on the UMAP 2023 website.</span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"><u>Personalized Recommender Systems</u></span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">This track invites works from researchers and practitioners on recommender</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">systems. In addition to mature research works addressing technical aspects of </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">recommendations, we welcome research contributions that address questions</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">related to user perception, decision-making, and the business value of</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">recommender systems.</span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"><u>Adaptive, Semantic, Knowledge, and Social Graphs</u></span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">This track welcomes works focused on the use of knowledge representations (i.e., </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">novel knowledge bases), graph algorithms (i.e., graph embedding techniques), and </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">social network analysis at the service of addressing all aspects of personalization,</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">user model building, and personal experience in online social systems. Moreover,</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">this track invites works in adaptive hypermedia, as well as semantic and social web.</span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"><u>Intelligent User Interfaces</u></span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">This track invites works exploring how to make the interaction between computers </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">and people smarter and more productive, leveraging solutions from</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">human-computer interaction, data mining, natural language processing,</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">information visualization, and knowledge representation and reasoning.</span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"><u>Personalizing Learning Experiences through User Modeling</u></span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">This track invites researchers, developers, and practitioners from various disciplines</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">to submit their innovative learning solutions, share acquired experiences, and</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">discuss their modeling challenges for personalized adaptive learning.</span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"><u>Fairness, Transparency, Accountability, and Privacy</u></span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">Researchers, developers, and practitioners have a social responsibility to account for </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">the impact that technologies have on individuals (users, providers, and other </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">stakeholders) and society. This track invites works related to the science of building, </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">maintaining, evaluating, and studying adaptive systems that are fair, transparent, </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">respectful of users’ privacy, beneficial to society, and accountable for their impacts.</span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"><u>Personalization for Persuasive and Behavior Change Systems</u></span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">This track invites submissions focused on personalization and tailoring for</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">persuasive technologies, including but not limited to personalization models, user </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">models, computational personalization, design, and evaluation methods. It also </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">welcomes work that brings attention to the user experience and designing </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">personalized and adaptive behavior change technologies.</span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"><u>Virtual Assistants, Conversational Interactions, and Personalized Human-robot </u></span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"><u>Interaction</u></span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">This track invites works investigating new models and techniques for adapting </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">synthetic companions (e.g., virtual assistants, chatbots, social robots) to individual </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">users. With the conversational modality so in vogue across disciplines, this track </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">welcomes work highlighting the model and deployment of synthetic companions</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">driven by conversational search and recommendation paradigms.</span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"><u>Research Methods and Reproducibility</u></span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">This track invites submissions on methodologies to evaluate personalized systems,</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">benchmarks, and measurement scales, with particular attention to the reproducibility</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">of results and techniques. Furthermore, the track looks for submissions that report </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">new insights from reproducing existing works.</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"> </span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 18px; color: #000000;"><b>Submission and Review Process</b></span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">Submissions for any of the aforementioned tracks should have a maximum length of </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">*14 pages* (excluding references) in the ACM new single-column format</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">(<a href="https://www.acm.org/publications/proceedings-template).">https://www.acm.org/publications/proceedings-template).</a> (Papers of any length up</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">to 14 pages are encouraged; reviewers will comment on whether the size is </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">appropriate for the contribution.) Additional review criteria and submission link will </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">be available shortly on the conference website: <a href="https://www.um.org/umap2023/ .">https://www.um.org/umap2023/ .</a></span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">Accepted papers will be included in the conference proceedings and presented at the</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">conference. At least one author should register for the conference by the early </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">registration date cut-off.</span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">UMAP uses a *double-blind* review process. Authors must omit their names and </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">affiliations from their submissions; they should also avoid obvious identifying </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">statements. For instance, citations to the authors' prior work should be in the third </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">person. Submissions not abiding by anonymity requirements will be desk rejected. </span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">UMAP has a *no dual submission* policy, which is why full paper submissions should</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">not be currently under review at another publication venue. Further, UMAP operates </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">under the ACM Conference Code of Conduct</span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">(<a href="https://www.acm.org/about-acm/policy-against-harassment).">https://www.acm.org/about-acm/policy-against-harassment).</a></span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 18px; color: #000000;"><b>Program Chairs</b></span></div>
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<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">•</span><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"> Julia Neidhardt, TU Wien, Austria </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">•</span><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"> Sole Pera, TU Delft, The Netherlands </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;"> </span></div>
<div style="text-align: left"><span style="font-family: Lucida Grande, Arial, Helvetica; font-size: 16px; color: #000000;">Contact information: umap2023-program@um.org</span></div>
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