WORKSHOPS
CRUM 2023: The first edition of the workshop on Context Representation in User Modelling
Organizers
Owen Conlan, ADAPT Centre, Trinity College Dublin
Judy Kay, University of Sydney, Australia
Jovan Jeromela, ADAPT Centre, Trinity College Dublin
Dipto Barman, ADAPT Centre, Trinity College Dublin
Hassan Zaal, ADAPT Centre, Trinity College Dublin
Alok Debnath, ADAPT Centre, Trinity College Dublin
Awais Akbar, ADAPT Centre, Trinity College Dublin
Description
Context, i.e. the information describing the situation of a user or any object deemed relevant in human-computer interaction, is a critical aspect of user modelling, adaptation, and personalisation. The exact meaning and realisation of contextual information can vary based on the application area but identifying such relevant information within an interactive situation can determine the appropriateness of the system’s behaviour. The workshop on Context Representation in User Modelling (CRUM) aims to become a place where novel and emerging context representation methods can be introduced while existing approaches can be highlighted, contrasted, and evaluated. We also welcome submissions tackling challenges in related areas, including the use of context information for explainability and context modelling for privacy within adaptive systems.
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ExUM 2023: 5th Workshop on Explainable User Models and Personalised Systems
Organizers
Cataldo Musto, University of Bari, Italy
Amra Delic, University of Sarajevo, Bosnia and Herzegovina.
Oana Inel , University of Zurich, Switzerland
Marco Polignano, University of Bari, Italy
Amon Rapp, University of Torino, Italy
Giovanni Semeraro, University of Bari, Italy
Jürgen Ziegler, University of Duisburg-Essen, Germany
Description
Adaptive and personalized systems have become pervasive technologies that are gradually playing an increasingly important role in our daily lives. Indeed, we are now exploited to interact every day with algorithms that help us in several scenarios, ranging from services that suggest us music to be listened to or movies to be watched, to personal assistants able to proactively support us in complex decision-making tasks. As the importance of such technologies in our everyday lives grows, it is fundamental that the internal mechanisms that guide these algorithms are as clear as possible. Unfortunately, the current research tends to go in the opposite direction, since most of the approaches try to maximize the effectiveness of the personalization strategy (e.g., recommendation accuracy) at the expense of the explainability and the transparency of the model. Several research lines are triggered by this question: building scrutable user models and transparent algorithms, analyzing the impact of opaque algorithms on final users, studying the role of explanation strategies, and investigating how to provide users with more control in the personalization and adaptation problems. The workshop aims to provide a forum for discussing such problems, challenges, and innovative research approaches in the area, by investigating the role of transparency and explainability in the recent methodologies for building user models or for developing personalized and adaptive systems.
GMAP 2023: 2nd Workshop on Group Modeling, Adaptation and Personalization
Organizers
Francesco Barile, Maastricht University, Netherlands
Amra Delić, University of Sarajevo, Bosnia and Herzegovina
Ladislav Peska, Charles University, Czech Republic
Isabella Saccardi, Utrecht University, Netherlands
Onuralp Ulusoy, Utrecht University, Netherlands
Federica Lucia Vinella, Utrecht University, Netherlands
Description
Although most existing recommender systems support single users, there are many scenarios where these systems target the needs of groups. Factors such as group mood, emotional contagion, and interpersonal relationships, are characteristics that are often ill-defined, tend to mutate over time, and are usually missing from the systems’ modeling, even though they play an indispensable part of group modeling. Furthermore, producing timely and accurate recommendations for groups that are explainable, fair, and privacy-protecting is a notoriously difficult challenge since group members may have divergent views and needs.
With the 2nd Workshop on Group Modeling, Adaptation and Personalization (GMAP), we propose a way to bring together a community of researchers focused on group modeling, adaptation, and personalization. The workshop will explore the challenges and opportunities associated with developing effective methods and tools to support group decision-making. It will bring together researchers from several disciplines, including Psychology, Computer Science, and Organizational Behavior, to discuss their latest research and ideas on this topic. Furthermore, the workshop will provide opportunities for participants to share their research and experiences, and to collaborate and network with other researchers in this field. By bringing together experts from different disciplines and perspectives, the workshop aims at fostering a vibrant and inclusive community of researchers who are committed to advancing our understanding of group modeling, adaptation, and personalization, identifying key challenges and opportunities in this area and developing a shared research agenda that will guide future works in the field.
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HAAPIE 2023: 8th International Workshop on Human Aspects in Adaptive and Personalized Interactive Environments
Organizers
Panagiotis Germanakos, SAP SE, DE
Vania Dimitrova, University of Leeds, UK
Ben Steichen, California State Polytechnic University, Pomona, USA
Bruce Ferwerda, Jönköping University, SE
Marko Tkalcic, University of Primorska in Koper, SI
Description
The vision of HAAPIE 2023 workshop is to bring more inclusively the “human-in-the-loop” in UMAP for increasing the usability, user experience and overall quality of systems and interactions. State-of-the-art approaches in adaptation and personalization research that consider information regarding the “traditional” user characteristics (i.e., experience, knowledge, interests, context), and related contextual or technology aspects (i.e., displays, connectivity, processing power) have shown significant improvements and benefits to the end-users. However, there is an urgent need for a step change in user modeling and adaptation that considers human aspects thoroughly, producing more holistic human-centered adaptation and personalization theories and practices. This requires broadening the scope including intrinsic human characteristics and abilities, such perceptual, personality, visual, cognitive, and emotional factors as well as other diversity parameters ranging from more recognizable user characteristics, such as culture, status, to more inherent ones, such as motivation, self-actualization, and socio-cultural behavior. Accordingly, main goal of HAAPIE 2023 is to bring together researchers and practitioners working in the areas of human aspects in adaptation and personalization to shape new human-centered adaptive interactive environments and personalized platforms that can contribute towards viable long-term solutions.
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PATCH 2023: The 14th International Workshop on Personalized Access to Cultural Heritage
Organizers
Liliana Ardissono, University of Torino, Italy
Noemi Mauro, University of Torino, Italy
Daniela Petrelli, Sheffield Hallam University, UK
George E. Raptis, Human Opsis, Greece
Alan Wecker, The University of Haifa, Israel
Description
Following the successful series of PATCH workshops, PATCH 2023, the new link in the long chain of PATCH workshops series, will be again the meeting point between state-of-the-art cultural heritage research and personalization – using any kind of technology, while focusing on ubiquitous and adaptive scenarios, to enhance the personal experience in cultural heritage sites. The workshop is aimed at bringing together researchers and practitioners who are working on various aspects of cultural heritage and are interested in exploring the potential of state of the art of mobile technology (onsite as well as online) to enhance the CH visit experience. The expected result of the workshop is a multidisciplinary research agenda that will inform future research directions and hopefully, forge some research collaborations.
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FairUMAP: 6th UMAP Workshop on Fairness in User Modeling, Adaptation, and Personalization
Organizers
Bamshad Mobasher, DePaul University, USA
Styliani Kleanthous, Open University of Cyprus
Jahna Otterbacher, Open University of Cyprus
Robin Burke, University of Colorado, Boulder, USA
Avital Shulner Tal, University of Haifa, Israel
Description
Personalization has become a ubiquitous and essential part of systems that help users find relevant information in today’s highly complex information-rich online environments. Machine learning, recommender systems, and user modeling are key enabling technologies that allow intelligent systems to learn from users and adapt their output to users’ needs and preferences. However, there has been a growing recognition that these underlying technologies raise novel ethical, legal, and policy challenges. It has become apparent that a single-minded focus on the user preferences has obscured other important and beneficial outcomes such systems must be able to deliver. System properties such as fairness, transparency, balance, openness to diversity, and other social welfare considerations are not captured by typical metrics based on which data-driven personalized models are optimized. Indeed, widely-used personalization systems in such popular sites such as Facebook, Google News and YouTube have been heavily criticized for personalizing information delivery too heavily at the cost of these other objectives. Bias, fairness, and transparency in machine learning are topics of considerable recent research interest. However, more work is needed to expand and extend this work into algorithmic and modeling approaches where personalization and user modeling are of primary importance. In particular, it is essential to address these challenges from the standpoint of understanding stereotypes in users’ behaviors and their influence on user or group decisions. The 5th Workshop on Fairness in User Modeling, Adaptation, and Personalization aims to bring together experts from academia and industry to discuss ethical, social, and legal concerns related to personalization and user modeling with the goal of exploring a variety of mechanisms and modeling approaches that help mitigate bias and achieve fairness in personalized systems.
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ADAPPT: Adaptive and Personalized Persuasive Technologies Workshop
Organizers
Kiemute Oyibo, York University, Canada
Ifeoma Adaji, University of British Columbia, Canada
Rita Orji, Dalhousie University, Canada
Jaap Ham, Eindhoven, University of Technology, Netherlands
Julita Vassileva, University of Saskatchewan, Canada
Description
Persuasive technologies are interactive systems intentionally designed to change behaviors and attitudes without coercion, deception or manipulation through persuasion and social influence. They have been applied in various domains (e.g., health, education, energy conservation) to promote positive behaviors. However, they are more likely to be effective if they are adapted and personalized to the target users. For example, a persuasive strategy that is effective for one target group may not be appropriate for another. Hence, to prevent creating one-size-fit-all persuasive apps that are ineffective, research on theorical models, frameworks, methods, techniques, and user evaluation is necessary to tailor and personalize the persuasive apps to their target audience. Our workshop aims to bring together persuasive technology researchers and practitioners working in the area of adaption and personalization, especially on emerging research, in various domains such as health, education, workplace, energy conservation, e-commerce, to mention but a few. To support emerging work in the early stages that has the potential to advance the field, the ADAPPT workshop will provide a platform for researchers and practitioners from academia and industry to network, present their work and deliberate on ensuing questions, contributions, and insights.
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