Workshop Day: July 8, 2018. All workshops are full-day.
Official Workshop Website: http://haapie.cs.ucy.ac.cy
Description: The vision of HAAPIE 2018 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 2018 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.
Official Workshop Website: http://teldh.dibris.unige.it/iuadapt/
Description: There is a general enthusiastic call for smart applications nowadays. People are now accustomed to mobile devices and require applications that fit and exploit this modality of interaction and are proactive to satisfy their needs.
All of these applications require a deep understanding of content, users, devices and situations where interaction happens. Semantics covers a significant role toward these goals.
At the same time, employing such sophisticated systems requires rigorous evaluation right from the beginning. With this workshop we want to raise awareness in the user modeling community for the significance of using multiple methods in the evaluation of recommender systems and other personalized systems. Employing a multi-method evaluation integrating a number of single methods allows for getting a more integrated and richer picture of user experience and quality drivers.
The objective of the Intelligent User-Adapted Interfaces: Design and Multi-Modal Evaluation workshop is to bring together experts and practitioners of user modeling, adaptive systems, recommenders and artificial Intelligence together with domain experts and ubiquitous computing researchers, in order to shape the next generation of ubiquitous, smart and adaptive application services.
Official Workshop Website: https://hum18.wordpress.com/
Description: The main goal of the workshop is to investigate novel methodologies to exploit data gathered from social networks and personal devices (smartphones, tracking devices) to build a new generation of personalized and intelligent systems in domains as diverse as health, learning, behavior change, e-government, smart cities (e.g., by combining mood data and music preferences data to provide recommendations on music to be listened).
Official Workshop Website: https://fairumap.wordpress.com/
Description: 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 and fairness 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 is of primary importance. The goal of this workshop is to bring together a growing community of experts from academia and industry to discuss ethical, social, and legal concerns related to personalization, and specifically to explore a variety of mechanisms and modeling approaches that help mitigate bias and achieve fairness in personalized systems.