- LPRS: 1st International Workshop on Learning Path Recommender Systems
- ExUM: Explainable User Models and Personalised Systems
- HAAPIE: Human Aspects in Adaptive and Personalized Interactive Environments
- ADAPPT: Adaptive and Personalized Persuasive Technology
- INSURANCE: Insurance, algorithmic decision-making, and discrimination
- APPS: Adaptive and Personalized Privacy and Security
- cAESAR: Adapted intEraction with SociAl Robots
- PATCH: International Workshop on Personalized Access to Cultural Heritage
- PICA: Towards a new generation of Personalized Intelligent Conversational Agents
- FairUMAP: Workshop on Fairness in User Modeling, Adaptation and Personalization
LPRS: 1st International Workshop on Learning Path Recommender Systems
The use of e-learning started to widespread in the beginning of the 2000’s as a complementary resource to classroom education. We then discovered that “one-size-fits-all” solutions are not effective to foster learning. The COVID pandemic then shifted things by making the use of e-learning no longer complementary but mandatory to teach. This whole context has contributed to the generation of an overwhelmingly amount of digital learning resources but not always providing the proper tools to handle them. The use of a learning-path is one of the ways to guide the students and avoid the cognitive overload, lack of motivation, and consequently dropout. This 1st International Workshop on Learning Path Recommendation Systems (LPRS) wants to receive and discuss papers that provide a way to guide the students in e-learning scenarios. Some general topics of interests are:
- Modeling of users and items
- New LPRS approaches
- Evaluation of LPRS
- Domain-specific LPRS
- Anne Boyer, Univ. of Lorraine, France
- José Palazzo M. de Oliveira, UFRGS, Brazil
- Guilherme M. Machado, Univ. de Lorraine, France
ExUM: Explainable User Models and Personalised Systems
Adaptive and personalized systems have become pervasive technologies which are gradually playing an increasingly important role in our daily lives. 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. ExUM workshop aims to provide a forum to discuss and investigate the role of transparency and explainability in the development of novel methodologies to build user models and personalized systems. Research lines of interest for ExUM include: building scrutable user models and transparent algorithms, analyzing the impact of opaque algorithms on final users, studying the role of explanation strategies, investigating how to provide users with more control in personalized and adaptive systems.
- Cataldo Musto, University of Bari, Italy
- Nava Tintarev, Maastricht University, the Netherlands
- Oana Inel, Delft University of Technology, the Netherlands
- Marco Polignano, University of Bari, Italy
- Giovanni Semeraro, University of Bari, Italy
- Jürgen Ziegler, University of Duisburg - Essen, Germany
HAAPIE: Human Aspects in Adaptive and Personalized Interactive Environments
The vision of HAAPIE 2021 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 as perceptual, personality, visual, cognitive, and emotional factors as well as other diversity parameters ranging from more recognizable user characteristics, such as age, culture, status, to more inherent ones, such as motivation, self-actualization, and socio-cultural behavior. Accordingly, main goal of HAAPIE 2021 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.
- Panagiotis Germanakos, SAP SE, Germany
- Vania Dimitrova, University of Leeds, UK
- Ben Steichen, California State Polytechnic University, Pomona, USA
- Alicja Piotrkowicz, Scaled Insights, UK & University of Leeds, UK
ADAPPT: Adaptive and Personalized Persuasive Technology
Research shows that personalizing digital technologies aimed at behavior change has the potential to make them more effective. Hence, every year at the Adaptive and Personalizing Persuasive Technology (ADAPPT) workshop, we bring together a wide range of researchers and practitioners from academia and industry with a common interest in advancing the field. We seek research efforts that focus on adapting, personalizing and/or tailoring persuasive systems to improve their motivational appeal and effectiveness. Due to the pandemic, the workshop will take the form of online presentations, discussions and deliberations. It will support an interactive forum structured in a way that encourages an active participation in the discussion of the presented papers and the ensuing questions and contributions. It will begin with a keynote address from an invited guest speaker from the field of UMAP, followed by a peer-reviewed paper presentation session, and a question-and-answer session.
- Kiemute Oyibo, University of Waterloo, Canada
- Ifeoma Adaji, University of Saskatchewan, Canada
- Rita Orji, Dalhousie University, Canada
- Jaap Ham, Eindhoven University of Technology, Netherlands
- Julita Vassileva, University of Saskatchewan, Canada
INSURANCE: Insurance, algorithmic decision-making, and discrimination
Insurance companies could use algorithmic systems to set premiums for individual consumers, or deny them insurance. More and more data become available for insurers for risk differentiation. For example, some insurers monitor people’s driving behaviour to estimate risks. To some extent, risk differentiation is necessary for insurance. And it could be considered fair when, e.g., high-risk drivers pay more.
But there are drawbacks. Algorithmic decision-making could lead, unintentionally, to discrimination on the basis of, for instance, ethnicity or gender. Too much personalised risk differentiation could also make insurance unaffordable for some people. Furthermore, risk differentiation might result in the poor paying more, thereby worsening economic inequality.
Our half-day workshop addresses these issues with participants from different disciplines (e.g., computer science, law, human- computer interaction, data justice, ethics, economy). It will include a panel, working groups to discuss questions triggered by the panel in-depth and a final presentation by each group.
- Frederik Zuiderveen Borgesius, iHub, Radboud University, the Netherlands
- Hanna Schraffenberger, iHub, Radboud University, the Netherlands
- Marvin van Bekkum, iHub, Radboud University, the Netherlands
APPS: Adaptive and Personalized Privacy and Security
Adaptive and personalized privacy and security in the context of interactive systems reflects the support such systems provide to end-users engaged in privacy- and/or security-related tasks. They require an understanding of user models which capture holistically the users’ physical characteristics (e.g., cultural, cognitive, age, habits), technology (e.g., standalone, mobile, mixed-virtual-augmented reality, wearables), and their interaction context (e.g., being on the move, social settings, spatial limitations). APPS 2021 aims to bring together researchers and practitioners working on diverse topics related to understanding and improving the usability of privacy and security systems, by applying user modeling, adaptation and personalization principles. Our special focus in 2021 will be on challenges and opportunities related to the Covid-19 outbreak for ensuring privacy and security of users’ interactions in online systems (like challenges for online distance learning, e-Government, e-Commerce, the need for touchless authentication, etc.).
- Argyris Constantinides, Cognitive UX LTD, Cyprus & University of Cyprus, Cyprus
- Marios Belk, Cognitive UX GmbH, Germany & University of Cyprus, Cyprus
- Christos Fidas, University of Patras, Greece
- Juliana Bowles, University of St. Andrews, UK
- Andreas Pitsillides, University of Cyprus, Cyprus
cAESAR: Adapted intEraction with SociAl Robots
Human Robot Interaction (HRI) is a field of study dedicated to understanding, designing, and evaluating robotic systems for use by, or with, humans. In HRI there is a consensus about the design and implementation of robotic systems that should be able to adapt their behavior on the basis of user actions and behavior. The robot should adapt to emotions, personalities, and it should also have a memory of past interactions with the user in order to become believable. This is of particular importance in the field of social robotics and social HRI. The aim of this Workshop is to bring together researchers and practitioners who are working on various aspects of social robotics and adaptive interaction. The expected result of the workshop is a multidisciplinary research agenda that will inform future research directions and hopefully, forge some research collaborations.
- Berardina de Carolis, University of Bari, Italy
- Cristina Gena, University of Torino, Italy
- Antonio Lieto, University of Torino, Italy
- Silvia Rossi, University of Naples Federico II, Italy
- Alessandra Sciutti, Italian Institute of Technology, Italy
PATCH: International Workshop on Personalized Access to Cultural Heritage
Following the successful series of PATCH workshops, PATCH 2021, 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.
- Liliana Ardissono, University of Torino, Italy
- Cristina Gena, University of Torino, Italy
- Tsvika Kuflik, The University of Haifa, Israel
- Noemi Mauro, University of Torino, Italy
- George E. Raptis, Human Opsis, Greece
- Alan Wecker, The University of Haifa, Israel
PICA: Towards a new generation of Personalized Intelligent Conversational Agents
The PICA workshop focuses on both long-term engaging spoken dialogue systems and text-based chatbots, as well as conversational recommender systems. Papers can be about different approaches to this: (pilot) evaluations, design guidelines, personalization, natural language processing, protection of privacy and (health) data, (cognitive) architectures and frameworks, implementations, context analyses. We are also very interested in studies on the effectiveness of behaviour change support systems and changing health related behaviour (such as quit smoking, lose weight, etc.). The main goal of the workshop is to stimulate discussion around problems, challenges, possible solutions and research directions regarding the exploitation of NLP and ML techniques to learn user features and use them to personalize the dialogue in the next generation of intelligent conversational agents.
- Iris Hendrickx, Centre for Language Studies, Radboud University, Netherlands
- Federica Cena, University of Torino, Italy
- Erkan Basar, Radboud University, Netherlands
- Luigi Di Caro, University of Torino, Italy
- Florian Kunneman, Vrije University, Netherlands
- Elena Musi, University of Liverpool, UK
- Cataldo Musto, University of Bari, Italy
- Amon Rapp, University of Torino, Italy
- Jelte van Waterschoot, Human Media Interaction, University of Twente, Netherlands
FairUMAP: Workshop on Fairness in User Modeling, Adaptation and Personalization
Machine learning, recommender systems, and user modeling are key enabling technologies used in personalized intelligent systems. However, there has been a growing recognition that these underlying technologies raise novel ethical, policy, and legal challenges. System properties such as fairness, transparency, balance, openness to diversity, and other social welfare considerations are not always captured by typical metrics based on which data-driven personalized models are optimized. 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 user modeling and personalization is of primary importance. In particular, it is essential to address these challenges from the standpoint of understanding stereotypes in users’ behavior and their influence on user or group decisions. The workshop aims to bring together a growing community of 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.
- Bamshad Mobasher, DePaul University, USA
- Styliani Kleanthous, Open University of Cyprus, Cyprus
- Bettina Berendt, KU Leuven, Belgium
- Jahna Otterbacher, Open University of Cyprus, Cyprus
- Robin Burke, University of Colorado, Boulder, USA
- Tsvi Kuflik, University of Haifa, Israel
- Avital Shukber Tal, University of Haifa, Israel