ACM UMAP – User Modelling, Adaptation and Personalization – is the premier international conference for researchers and practitioners working on systems that adapt to individual users, to groups of users, and that collect, represent, and model user information. ACM UMAP is the successor to the biennial User Modeling (UM) and Adaptive Hypermedia and Adaptive Web-based Systems (AH) conferences that were merged in 2009. It is sponsored by ACM SIGCHI and SIGWEB, and organized with User Modeling Inc. as the Steering Committee. The proceedings are published by ACM and will be part of the ACM Digital Library.
ACM UMAP 2019 will be held in Larnaca (Cyprus) from June 9-12, 2019.
Marko Tkalcic, Free University of Bozen-Bolzano, email@example.com
Alan Said, University of Skövde, firstname.lastname@example.org
Personalized, computer-generated recommendations have become a pervasive feature of today’s online world. The underlying recommender systems are designed to help users and providers in a number of ways. From a user’s viewpoint, for example, these systems assist consumers in finding relevant things within large item collections. On the other hand, from a provider’s perspective, recommenders have also shown to be valuable tools to steer consumer behavior. From a technical perspective, the design of such systems requires the careful consideration of various aspects, including the choice of the user modeling approach, the underlying recommendation algorithm, and the user interface. This track aims to provide a forum for researchers and practitioners to discuss open challenges, latest solutions and novel research approaches in the field of recommender systems. Besides the above-mentioned technical aspects, works are also particularly welcome that address questions related to the user perception and the business value of recommender systems.
Topics include (but are not limited to):
Liliana Ardissono, University of Torino, email@example.com
Katrien Verbert, KU Leuven, firstname.lastname@example.org
Adaptive hypermedia and adaptive web explore alternatives to the traditional “one-size-fits-all” approach in the development of web and hypermedia systems. Adaptive hypermedia and adaptive web systems build a model of the interests, preferences and knowledge of each individual user, and use this model in order to adapt the behavior of hypermedia and web systems to the needs of that user. Semantic web frequently serves as an infrastructure to enable adaptive and personalized Web systems. Semantic web technology targets the use of explicit semantics and metadata to help web systems perform the desired functionality: this implies the use of linked data from the web, the use of ontologies in models, or the use of metadata in user interfaces, as well as the use of ontologies for information integration. This track aims to provide a forum to researchers to discuss open research problems, solid solutions, latest challenges, novel applications and innovative research approaches in adaptive hypermedia and semantic web.
Li Chen, Hong Kong Baptist University, email@example.com
Jingtao Wang, Google, firstname.lastname@example.org
Intelligent User Interfaces aim to improve the interaction between computer systems and human users by means of Artificial Intelligence. The systems support and complement different types of abilities that are normally unavailable in the context of human-only cognition. Previous work has found that humans do not always make the best possible decisions when working together with computer systems. By designing and deploying improved forms of support for interactive collaboration between human decision makers and systems, we can enable decision making processes that better leverage the strengths of both collaborators. More generally this research track can be characterized by exploring how to make the interaction between computers and people smarter and more productive, which may leverage solutions from human-computer interaction, data mining, natural language processing, information visualization, and knowledge representation and reasoning
Ilaria Torre, University of Genova, email@example.com
Osnat Mokryn, firstname.lastname@example.org
The social web is continuously growing and social platforms are a fundamental part of our life. Mediated communication is becoming the primary form of communication for young people, and adults follow in increasing numbers. Online communication is increasingly enriched by the use of memes, pictures, audio and video, though language (textual and oral) remains a fundamental tool with which people interact, convey their opinions, construct and determine their social identity. Lifelogging data (e.g., health, fitness, food) is growing as well on the social web. This type of personal information source, gathered for private use through personal devices, is now often shared in online communities. These trends open new challenges for research: how to harness the power of collective intelligence and quantified self data in online social platforms to identify social identities, how to exploit continuous feedback threads, and how to improve the individual user experience on the social web.
We invite original submissions addressing all aspects of personalization, user models building and personal experience in online social systems.
Jesús G. Boticario, UNED, email@example.com
Inge Molenaar, Radboud University, firstname.lastname@example.org
At large there is an on-going “fusion” between humans and technological systems. The ongoing integration of devices into our daily lives furthers the integration of technology in human learning. With technology increasingly gaining more data and intelligence, a new era of technology-enhanced adaptive learning is emerging. Consequently, the interactions between learners, teachers and technology are becoming increasingly complex. Learning is a positioned as a complex human process that involves cognitive, metacognitive, motivational, affective and psychomotor aspects which interact with the learning context. Smart technological solutions are increasingly able to identify and model the learner needs on these five aspects and accordingly provide personalized support that can improve the effectiveness, efficiency and satisfaction of learning experiences.
Current research in artificial intelligence combined with data science and learning analytics bring new opportunities to recognize, and effectively support individual learners’ needs and orchestrate collaborate and classroom learning with intelligent learning solutions, and augment teachers in blended learning situations. The aim of this track is to foreground the systematic complexity of human learning and use systematic analytic approaches to measure, diagnose and support human learning with technologies. This covers not only formal educational settings, but also lifelong learning requirements (including workplace training) as well as the acquisition of skills informal learning settings (e.g., in daily activities, serious games, sports, healthcare, wellbeing, etc.).
To address the wide spectrum of modeling issues and challenges that can be raised, contributions from various research areas are welcome. Therefore, this track invites researchers, developers, and practitioners from various disciplines to present their innovative adaptive learning solutions, share acquired experience, and discuss the main modeling challenges for technology enhanced adaptive learning.
Bart Knijnenburg, Clemson University, email@example.com
Esma Aimeur, University of Montreal, firstname.lastname@example.org
Adaptive systems researchers and developers have a social responsibility to care about their users. This involves building, maintaining, evaluating, and studying adaptive systems that are fair, transparent, and protect users' privacy. We invite papers that study, in the context of UMAP, the topics of privacy (as well as innovative means to resolve privacy problems through algorithms, interfaces, or other technical or non-technical means), fairness (covering the spectrum from algorithmic fairness to social implications of adaptive systems), and transparency (as a concept of system usability as well as a means to resolve problems with privacy and fairness). Beyond this we encourage authors to submit to this track any work that ascribes to or advances the general idea of "adaptive systems that care”.
Markus Schedl, University of Linz, email@example.com
Nava Tintarev, TU Delft, firstname.lastname@example.org
Music access systems (e.g., search, retrieval, and recommendation systems) have experienced a boom during the past decade due to the availability of huge music catalogs to users, anywhere and anytime. These systems record information on user behavior in terms of actions on music items, such as play, skip, or playlist creation and modification. As a result, an abundance of user and usage data has been collected and is available to companies and academics, allowing for user profiling and to create and improve personalized music access. This track addresses unsolved challenges in this area relating to user understanding and modeling, personalization in recommendation and retrieval systems, modeling usage context, and adapting interactive intelligent music interfaces. This track aims to provide a forum for researchers and practitioners for the latest research on user modeling and personalization for finding, making, and interacting with music.
Christoph Trattner, University of Bergen, email@example.com
David Elsweiler, University of Regensburg, firstname.lastname@example.org
Growing health issues and rising treatment costs mean that technological systems are increasingly important for global health. Personalised systems, tailored to the needs and behaviours of individual patients, are one of the promising approaches to health promotion by encouraging lifestyle change, managing treatment programmes and providing doctors and other healthcare providers with detailed individualized feedback. The challenges to developing such systems, which model user needs and preferences, as well as appropriate medical knowledge to provide assistance and recommendations are plentiful. The diverse technologies which could potentially feature in solutions are equally vast, ranging from AI systems to sensors, from mobile computing, augmented reality and visualization, to mining the web or other data streams to learn about health issues and user behaviour. In this track we invite scholars working in these or related areas to contribute to the discourse on how technology can promote health. This track aims to provide a forum to researchers to discuss open research problems, solid solutions, latest challenges, novel applications and innovative research approaches and in doing so to strengthen the community of researchers working on Personalized Health and attract representatives from from diverse scholarly backgrounds ranging from computer and information science to public health, epidemiology, psychology, medicine, nutrition and fitness.
Papers should be submitted through EasyChair: https://easychair.org/conferences/?conf=acmumap2019
The ACM User Modeling, Adaptation, and Personalization (ACM UMAP) 2019 Conference will include high quality peer-reviewed papers related to the above key areas. Maintaining the high quality and impact of the ACM UMAP series, each paper will have three reviews by program committee members and a meta-review presenting the reviewers’ consensual view; the review process will be coordinated by the program chairs in collaboration with the corresponding area chairs
Long (8 pages + references) and Short (4 pages + references) papers in ACM style Peer reviewed, original, and principled research papers addressing both the theory and practice of UMAP and papers showcasing innovative use of UMAP and exploring the benefits and challenges of applying UMAP technology in real-life applications and contexts are welcome.
Long papers should present original reports of substantive new research techniques, findings, and applications of UMAP. They should place the work within the field and clearly indicate innovative aspects. Research procedures and technical methods should be presented in sufficient detail to ensure scrutiny and reproducibility. Results should be clearly communicated and implications of the contributions/findings for UMAP and beyond should be explicitly discussed.
Short papers should present original and highly promising research or applications. Merit will be assessed in terms of originality and importance rather than maturity, extensive technical validation, and user studies.
Separation of long and short papers will be strictly enforced so papers will not compete across categories, but only within each category. Papers that receive high scores and are considered promising by reviewers, but didn’t make the acceptance cut, will be directed to the poster session of the conference and will be invited to be resubmitted as posters.
Papers must be formatted using the ACM SIG Standard (SIGCONF) proceedings template: https://www.acm.org/publications/proceedings-template.
Please note that ACM changed its templates at the start of 2017, so please ensure that you use the new template and do not reuse an old template.
All accepted papers will be published by ACM and will be available via the ACM Digital Library. At least one author of each accepted paper must register for the conference and present the paper there.
AUTHORS TAKE NOTE: The official publication date is the date the proceedings are made available in the ACM Digital Library. This date may be up to two weeks prior to the first day of your conference. The official publication date affects the deadline for any patent filings related to published work. (For those rare conferences whose proceedings are published in the ACM Digital Library after the conference is over, the official publication date remains the first day of the conference.)
Abstract: January 25, 2019
Full paper: February 1, 2019
Notification: March 11, 2019
Camera-ready: April 3, 2019
Adjunct proceedings, camera ready: April 15, 2018
Note: The submissions times are 11:59pm AoE time (Anywhere on Earth)
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