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<font face='Lucida Grande' size='4'><b>*** LAST MILE FOR PAPER SUBMISSION *** <br></b><br>27th ACM International Conference on User Modeling, Adaptation<br>and Personalization (ACM UMAP 2019)<br><br>“Making Personalization Transparent: Giving control back to the User"<br><br>Golden Bay Beach Hotel 5*, Larnaca, Cyprus, June 9-12, 2019<br><br><a href="http://www.cs.ucy.ac.cy/~george/lm/lm.php?tk=c2NlLmNhcmxldG9uLmNhICwJCQlmZy1hcmNAbGlzdHMudW5pLXBhZGVyYm9ybi5kZQlUaGUgMjd0aCBBQ00gQ29uZmVyZW5jZSBvbiBVc2VyIE1vZGVsaW5nLCBBZGFwdGF0aW9uIGFuZCBQZXJzb25hbGl6YXRpb24gKFVNQVAgMjAxOSk6IExhc3QgTWlsZSBmb3IgUGFwZXIgU3VibWlzc2lvbgkzMzcJTGlzdHMJMTQyCWNsaWNrCXllcwlubw==&url=https%3A%2F%2Fwww.um.org%2Fumap2019%2F">https://www.um.org/umap2019/</a><br></font><font face='Lucida Grande'><br><br><u>Abstracts due</u>: January 25, 2019 (mandatory)<br><u>Papers due</u>: February 1, 2019<br><br><br><br><b><u>BACKGROUND AND SCOPE<br></u></b><br>ACM UMAP, "User Modeling, Adaptation and Personalization", is the premier<br>international conference for researchers and practitioners working on<br>systems that adapt to individual users, to groups of users, and that collect,<br>represent, and model user information. ACM UMAP is sponsored by ACM<br>SIGCHI and SIGWEB. The proceedings are published by ACM and will be part<br>of the ACM Digital Library.<br><br>ACM UMAP covers a wide variety of research areas where personalization<br>and adaptation may be applied. This include (but is in no way limited to) a<br>number of domains in which researchers are engendering significant<br>innovations based on advances in user modeling and adaptation,<br>recommender systems, adaptive educational systems, intelligent user<br>interfaces, e-commerce, advertising, digital humanities, social networks,<br>personalized health, entertainment, and many more. <br><br>This year the conference hosts three new tracks, one on privacy and<br>fairness, one on personalized music access, and one on personalized health.<br><br><br><b><u>CONFIRMED INVITED SPEAKERS</u></b><br><br>• Marios Avraamides, University of Cyprus<br>• Judith Masthoff, Utrecht University<br>• Mounia Lalmas-Roelleke, Spotify London<br><br><br><b><u>CONFERENCE TRACKS<br></u></b><br><u>Track 1 - Personalized Recommender Systems<br></u><br><u>Chairs:</u><br>Marko Tkalcic, Free University of Bozen-Bolzano, marko.tkalcic@unibz.it<br>Alan Said, University of Skövde, alansaid@acm.org<br><br>Personalized, computer-generated recommendations have become a<br>pervasive feature of today’s online world. The underlying recommender<br>systems are designed to help users and providers in a number of ways.<br>From a user’s viewpoint, for example, these systems assist consumers in<br>finding relevant things within large item collections. On the other hand,<br>from a provider’s perspective, recommenders have also shown to be<br>valuable tools to steer consumer behavior. From a technical perspective,<br>the design of such systems requires the careful consideration of various<br>aspects, including the choice of the user modeling approach, the underlying<br>recommendation algorithm, and the user interface. This track aims to provide<br>a forum for researchers and practitioners to discuss open challenges, latest<br>solutions and novel research approaches in the field of recommender<br>systems. Besides the above-mentioned technical aspects, works are also<br>particularly welcome that address questions related to the user perception<br>and the business value of recommender systems.<br><br>Topics include (but are not limited to):<br><br>• Recommendation algorithms<br>• Recommender and personalization system evaluation<br>• User modeling and preference elicitation<br>• Users’ perception of recommender systems<br>• Business value of recommendation systems and multi-stakeholder<br> environments<br>• Explanations and trust<br>• Context-aware recommendation algorithms<br>• Recommending to groups of users<br>• Case studies of real-world implementations<br>• Novel, Psychology-informed User- and Item-modeling<br><br><u>Track 2 - Adaptive Hypermedia And The Semantic Web<br></u><br><u>Chairs</u>:<br>Liliana Ardissono, University of Torino, liliana.ardissono@unito.it<br>Katrien Verbert, KU Leuven, katrien.verbert@cs.kuleuven.be<br><br>Adaptive hypermedia and adaptive web explore alternatives to the traditional<br>“one-size-fits-all” approach in the development of web and hypermedia<br>systems. Adaptive hypermedia and adaptive web systems build a model of<br>the interests, preferences and knowledge of each individual user, and use<br>this model in order to adapt the behavior of hypermedia and web systems to<br>the needs of that user. Semantic web frequently serves as an infrastructure<br>to enable adaptive and personalized Web systems. Semantic web technology<br>targets the use of explicit semantics and metadata to help web systems<br>perform the desired functionality: this implies the use of linked data from<br>the web, the use of ontologies in models, or the use of metadata in user<br>interfaces, as well as the use of ontologies for information integration. This<br>track aims to provide a forum to researchers to discuss open research<br>problems, solid solutions, latest challenges, novel applications and innovative<br>research approaches in adaptive hypermedia and semantic web.<br><br>Topics include (but are not limited to):<br><br>• Web user profiles<br>• Adaptive navigation support<br>• Personalized search<br>• Web content adaptation<br>• Analytics of web user data<br>• Adaptive web sites and portals<br>• Adaptive books and textbooks<br>• Social navigation and social search<br>• Navigation support in continuous media and virtual environments<br>• Usability engineering for adaptive hypermedia and web systems<br>• Novel methodologies for evaluating adaptive hypermedia and web systems<br>• Semantic Web technologies for web personalization<br>• Ontology-based data access and integration/exchange on the adaptive web<br>• Ontology engineering and ontology patterns for the adaptive web<br>• Ontology-based user models<br>• Semantic social network mining, analysis, representation, and management<br>• Crowdsourcing semantics; methods, dynamics, and challenges<br>• Semantic Web and Linked Data for adaptation<br><br><u>Track 3 - Intelligent User Interfaces<br></u><br><u>Chairs</u>:<br>Li Chen, Hong Kong Baptist University, lichen@comp.hkbu.edu.hk<br>Jingtao Wang, Google, jingtaow@acm.org <br><br>Intelligent User Interfaces aim to improve the interaction between computer<br>systems and human users by means of Artificial Intelligence. The systems<br>support and complement different types of abilities that are normally<br>unavailable in the context of human-only cognition. Previous work has found<br>that humans do not always make the best possible decisions when working<br>together with computer systems. By designing and deploying improved forms<br>of support for interactive collaboration between human decision makers and<br>systems, we can enable decision making processes that better leverage the<br>strengths of both collaborators. More generally this research track can be<br>characterized by exploring how to make the interaction between computers<br>and people smarter and more productive, which may leverage solutions from<br>human-computer interaction, data mining, natural language processing,<br>information visualization, and knowledge representation and reasoning.<br><br>Topics include (but are not limited to):<br><br>• Adaptive personal virtual assistants (e.g., interaction with robots)<br>• Adapting natural interaction (e.g., natural language, speech, gesture)<br>• Intelligent user interfaces based on sensor data (UIs for cars, fridges, etc.)<br>• Multi-modal interfaces (speech, gestures, eye gaze, face, physiological info, etc.)<br>• Intelligent wearable and mobile interfaces<br>• Smart environments and tangible computing<br>• Transparency and control of decision support systems(e.g., semi-autonomous systems)<br>• Explainable intelligent user interfaces<br>• Affective and aesthetic interfaces<br>• Tailored persuasion and argumentation interfaces<br>• Tailored decision support (e.g., over- and under-reliance in uncertain domains)<br>• Adaptive information visualization<br>• Scalability of intelligent user interfaces to access huge datasets<br>• User-centric studies of interactions with intelligent user interfaces<br>• Novel datasets and use cases for intelligent user interfaces<br>• Evaluations of intelligent user interfaces<br><br><u>Track 4 - Personalized Social Web<br></u><br><u>Chairs</u>:<br>Ilaria Torre, University of Genova, ilaria.torre@unige.it<br>Osnat Mokryn, omokryn@univ.haifa.ac.il<br><br>The social web is continuously growing and social platforms are a<br>fundamental part of our life. Mediated communication is becoming the<br>primary form of communication for young people, and adults follow in<br>increasing numbers. Online communication is increasingly enriched by the<br>use of memes, pictures, audio and video, though language (textual and oral)<br>remains a fundamental tool with which people interact, convey their opinions,<br>construct and determine their social identity. Lifelogging data (e.g., health,<br>fitness, food) is growing as well on the social web. This type of personal<br>information source, gathered for private use through personal devices, is now<br>often shared in online communities. These trends open new challenges for<br>research: how to harness the power of collective intelligence and quantified<br>self data in online social platforms to identify social identities, how to exploit<br>continuous feedback threads, and how to improve the individual user<br>experience on the social web. <br><br>We invite original submissions addressing all aspects of personalization,<br>user models building and personal experience in online social systems.<br><br>Topics include (but are not limited to):<br><br>• Personalization of the web experience in social systems<br>• Adaptations based on personality, society, and culture<br>• Personalization algorithms and protocols inspired by human societies<br>• Social recommendation<br>• Identifying social identities in social media<br>• Social and crowd-generated data for adaptation<br>• Personalized information retrieval<br>• Exploiting quantified self data on the social web of things<br>• Data-driven approaches for personalization<br>• Modeling individuals, groups, and communities<br>• Collective intelligence and experience mining<br>• Pattern and behaviour discovery in social network analysis<br>• Opinion mining for user modeling<br>• Sentiment analysis<br>• Topic modeling for online conversations and short texts<br>• Privacy, perceived security, and trust in social systems<br>• Ethical issues involved in studying the social web<br>• User awareness and control<br>• Evaluation methodologies for the social web<br><br><u>Track 5 - Technology-Enhanced Adaptive Learning<br></u><br><u>Chairs</u>:<br>Jesús G. Boticario, UNED, jgb@dia.uned.es<br>Inge Molenaar, Radboud University, i.molenaar@pwo.ru.nl<br><br>At large there is an on-going “fusion” between humans and technological<br>systems. The ongoing integration of devices into our daily lives furthers the<br>integration of technology in human learning. With technology increasingly<br>gaining more data and intelligence, a new era of technology-enhanced<br>adaptive learning is emerging. Consequently, the interactions between<br>learners, teachers and technology are becoming increasingly complex.<br>Learning is a positioned as a complex human process that involves cognitive,<br>metacognitive, motivational, affective and psychomotor aspects which<br>interact with the learning context. Smart technological solutions are<br>increasingly able to identify and model the learner needs on these five<br>aspects and accordingly provide personalized support that can improve the<br>effectiveness, efficiency and satisfaction of learning experiences.<br><br>Current research in artificial intelligence combined with data science and<br>learning analytics bring new opportunities to recognize, and effectively<br>support individual learners’ needs and orchestrate collaborate and<br>classroom learning with intelligent learning solutions, and augment teachers<br>in blended learning situations. The aim of this track is to foreground the<br>systematic complexity of human learning and use systematic analytic<br> approaches to measure, diagnose and support human learning with<br>technologies. This covers not only formal educational settings, but also<br>lifelong learning requirements (including workplace training) as well as the<br>acquisition of skills informal learning settings (e.g., in daily activities, serious<br>games, sports, healthcare, wellbeing, etc.).<br><br>To address the wide spectrum of modeling issues and challenges that can be<br>raised, contributions from various research areas are welcome. Therefore,<br>this track invites researchers, developers, and practitioners from various<br>disciplines to present their innovative adaptive learning solutions, share<br>acquired experience, and discuss the main modeling challenges for<br>technology enhanced adaptive learning.<br><br>Topics include (but are not limited to):<br><br>• Domain, learner, teacher and context modeling<br>• Modeling cognitive, metacognitive, motivational, affective and psychomotor aspects of learning<br>• Diagnosis of learner needs and calibration of support and feedback Adaptive and personalized support for learning<br>• Dealing with ethical issues involved in detecting and modeling a widerrange of information sources (e.g., information from novel sensingdevices, ambient intelligent features) that may affect learning<br>• Management of large, open, and public datasets for educational data mining<br>• Agent-based learning environments and virtual pedagogical agents<br>• Open corpus personalized learning<br>• Collaborative and group learning<br>• Adaptive technologies to orchestrated classroom Learning<br>• Personalized teachers awareness and support tools<br>• Multimodal learning analytics to personalize learning<br>• UMAP aspects in specific learning solutions: educational recommender systems, intelligent tutoring systems, serious games, personal learning environments, MOOCs<br>• Wearable technologies and augmented reality in adaptive personalized learning<br>• Processing collected data for UMAP: educational data mining, learning analytics, big data, deep learning.<br>• Semantic web and ontologies for e-learning<br>• Interoperability, portability, and scalability issues<br>• Case studies in real-world educational settings<br>• New methodologies to develop user-centered highly personalized learning solutions<br><br><u>Track 6 - Privacy And Fairness<br></u><br><u>Chairs</u>:<br>Bart Knijnenburg, Clemson University, bartk@clemson.edu<br>Esma Aimeur, University of Montreal, aimeur@iro.umontreal.ca<br><br>Adaptive systems researchers and developers have a social responsibility to<br>care about their users. This involves building, maintaining, evaluating, and<br>studying adaptive systems that are fair, transparent, and protect users'<br>privacy. We invite papers that study, in the context of UMAP, the topics of<br>privacy (as well as innovative means to resolve privacy problems through<br>algorithms, interfaces, or other technical or non-technical means), fairness<br>(covering the spectrum from algorithmic fairness to social implications of<br>adaptive systems), and transparency (as a concept of system usability as<br>well as a means to resolve problems with privacy and fairness). Beyond this<br>we encourage authors to submit to this track any work that ascribes to or<br>advances the general idea of "adaptive systems that care”.<br><br><b>Privacy topics</b>:<br>• Analysis of privacy implications of user modeling<br>• Privacy compliance<br>• Algorithmic solutions to privacy<br>• Architectural solutions to privacy<br>• Interactive solutions to privacy<br>• Usable privacy for adaptive systems<br>• User perceptions of privacy in UMAP applications<br>• Studies of users’ privacy-related behaviors in UMAP applications<br>• Descriptions or evaluations of privacy-settings user interfaces<br>• Privacy prediction / personalization<br>• User-tailored approaches to privacy<br>• Privacy education for user modeling<br>• Modeling of data protection and privacy requirements<br>• Economics of privacy and personal data<br>• Measuring privacy<br><br><b>Fairness topics:</b><br>• Ethical considerations for user modeling<br>• UMAP applications for underrepresented groups<br>• Cultural differences (e.g. culture-aware user modeling)<br>• Bias and discrimination in user modeling<br>• Imbalance in meeting the needs of different groups of users<br>• Balancing needs of users versus system owners<br>• Ethics of explore/exploit strategies or A/B testing<br>• ‘Filter bubble’ or ‘balkanization’ effects<br>• Enhancing/embracing diversity in user modeling<br>• Algorithmic methods for increasing fairness<br>• User perceptions of fairness<br>• Measuring fairness<br><br><b>Transparency topics:</b><br>• User perceptions of transparency<br>• Transparent algorithms<br>• Interface innovations that increase transparency<br>• Explanations for transparency<br>• Visualizations for transparency<br>• Adaptive systems for self-actualization<br>• (User-centric) evaluations of methods that increase transparency<br>• Measuring transparency<br><br><u>Track 7 - Personalized Music Access<br></u><br><u>Chairs</u>:<br>Markus Schedl, University of Linz, markus.schedl@jku.at<br>Nava Tintarev, TU Delft, n.tintarev@tudelft.nl<br><br>Music access systems (e.g., search, retrieval, and recommendation systems)<br>have experienced a boom during the past decade due to the availability of<br>huge music catalogs to users, anywhere and anytime. These systems record<br>information on user behavior in terms of actions on music items, such as<br>play, skip, or playlist creation and modification. As a result, an abundance of<br>user and usage data has been collected and is available to companies and<br>academics, allowing for user profiling and to create and improve personalized<br>music access. This track addresses unsolved challenges in this area relating<br>to user understanding and modeling, personalization in recommendation and<br>retrieval systems, modeling usage context, and adapting interactive<br>intelligent music interfaces. This track aims to provide a forum for<br>researchers and practitioners for the latest research on? user modeling and<br>personalization for finding, making, and interacting with music.<br><br>Topics include (but are not limited to):<br><br>• Personalized music preference elicitation and preference learning<br>• Psychological modeling of music listeners (e.g., personality, emotion, etc.)<br>• Subjective perceptions of music (e.g., similarity, mood, tempo) social and cultural aspects of listening behavior (e.g., for group recommenders)<br>• Applications for personalized music consumption and creation<br>• Personalized playlist generation and continuation (e.g., sequences and transitions)<br>• Personalized music interaction and interface paradigms (e.g., visualization, VR)<br>• Explainability, transparency, and fairness in personalized music<br>• Systems user-centric performance measures (e.g., diversity, novelty, serendipity, etc.)<br>• Datasets (including benchmarks) for personalizing music retrieval and recommendation<br><br><u>Track 8 - Personalized Health<br></u><br><u>Chairs</u>:<br>Christoph Trattner, University of Bergen, trattner.christoph@gmail.com<br>David Elsweiler, University of Regensburg, david@elsweiler.co.uk<br><br>Growing health issues and rising treatment costs mean that technological<br>systems are increasingly important for global health. Personalised systems,<br>tailored to the needs and behaviours of individual patients, are one of the<br>promising approaches to health promotion by encouraging lifestyle change,<br>managing treatment programmes and providing doctors and other<br>healthcare providers with detailed individualized feedback. The challenges to<br>developing such systems, which model user needs and preferences, as well as<br>appropriate medical knowledge to provide assistance and recommendations<br>are plentiful. The diverse technologies which could potentially feature in<br>solutions are equally vast, ranging from AI systems to sensors, from mobile<br>computing, augmented reality and visualization, to mining the web or other<br>data streams to learn about health issues and user behaviour. In this track we<br>invite scholars working in these or related areas to contribute to the discourse<br>on how technology can promote health. This track aims to provide a forum to<br>researchers to discuss open research problems, solid solutions, latest<br>challenges, novel applications and innovative research approaches and in<br>doing so to strengthen the community of researchers working on<br>Personalized Health and attract representatives from from diverse scholarly<br>backgrounds ranging from computer and information science to public<br>health, epidemiology, psychology, medicine, nutrition and fitness.<br><br>Topics include (but are not limited to):<br><br>• Algorithms and Recommendation Strategies to increase health<br>• Mobile health<br>• Quantified self<br>• Applied data analytics and modeling for health<br>• Health risk modeling and forecasting<br>• Systems for Preventative Measures<br>• Medical Evaluation Techniques<br>• Domain Knowledge Representation<br>• Behavioral Interventions: Persuasion/Nudging/Behavioral Change<br>• HCI, Interfaces and Visualisations for health<br>• Regulations and Standards<br>• Human/ Expert-in-the-Loop<br>• Gamification and Serious Games<br>• Privacy, Trust, Ethics<br>• Datasets<br><br><br><b><u>SUBMISSION AND REVIEW PROCESS<br></u></b><br>Papers should be submitted through EasyChair:<br><a href="http://www.cs.ucy.ac.cy/~george/lm/lm.php?tk=c2NlLmNhcmxldG9uLmNhICwJCQlmZy1hcmNAbGlzdHMudW5pLXBhZGVyYm9ybi5kZQlUaGUgMjd0aCBBQ00gQ29uZmVyZW5jZSBvbiBVc2VyIE1vZGVsaW5nLCBBZGFwdGF0aW9uIGFuZCBQZXJzb25hbGl6YXRpb24gKFVNQVAgMjAxOSk6IExhc3QgTWlsZSBmb3IgUGFwZXIgU3VibWlzc2lvbgkzMzcJTGlzdHMJMTQyCWNsaWNrCXllcwlubw==&url=https%3A%2F%2Feasychair.org%2Fconferences%2F%3Fconf%3Dacmumap2019">https://easychair.org/conferences/?conf=acmumap2019</a><br><br>The ACM User Modeling, Adaptation, and Personalization (ACM UMAP) 2019<br>Conference will include high quality peer-reviewed papers related to the<br>above key areas. Maintaining the high quality and impact of the ACM UMAP<br>series, each paper will have three reviews by program committee members<br>and a meta-review presenting the reviewers’ consensual view; the review<br>process will be coordinated by the program chairs in collaboration with the<br>corresponding area chairs.<br><br>Long (8 pages + references) and Short (4 pages + references) papers in ACM<br>style, peer reviewed, original, and principled research papers addressing both<br>the theory and practice of UMAP and papers showcasing innovative use of<br>UMAP and exploring the benefits and challenges of applying UMAP<br>technology in real-life applications and contexts are welcome.<br><br>Long papers should present original reports of substantive new research<br>techniques, findings, and applications of UMAP. They should place the work<br>within the field and clearly indicate innovative aspects. Research procedures<br>and technical methods should be presented in sufficient detail to ensure<br>scrutiny and reproducibility. Results should be clearly communicated and<br>implications of the contributions/findings for UMAP and beyond should be<br>explicitly discussed.<br><br>Short papers should present original and highly promising research or<br>applications. Merit will be assessed in terms of originality and importance<br>rather than maturity, extensive technical validation, and user studies.<br><br>For both long papers and short paper submissions, it is not required to<br>anonymize the manuscripts, i.e., ACM UMAP will apply a single-blind<br>reviewing process.<br><br>Separation of long and short papers will be strictly enforced so papers will<br>not compete across categories, but only within each category. Papers that<br>receive high scores and are considered promising by reviewers, but didn’t<br>make the acceptance cut, will be directed to the poster session of the<br>conference and will be invited to be resubmitted as posters.<br><br>Papers must be formatted using the ACM SIG Standard (SIGCONF) proceedings<br>template: <a href="http://www.cs.ucy.ac.cy/~george/lm/lm.php?tk=c2NlLmNhcmxldG9uLmNhICwJCQlmZy1hcmNAbGlzdHMudW5pLXBhZGVyYm9ybi5kZQlUaGUgMjd0aCBBQ00gQ29uZmVyZW5jZSBvbiBVc2VyIE1vZGVsaW5nLCBBZGFwdGF0aW9uIGFuZCBQZXJzb25hbGl6YXRpb24gKFVNQVAgMjAxOSk6IExhc3QgTWlsZSBmb3IgUGFwZXIgU3VibWlzc2lvbgkzMzcJTGlzdHMJMTQyCWNsaWNrCXllcwlubw==&url=https%3A%2F%2Fwww.acm.org%2Fpublications%2Fproceedings-template">https://www.acm.org/publications/proceedings-template</a> .<br><br>Please note that ACM changed its templates at the start of 2017, so please<br>ensure that you use the new template and do not reuse an old template.<br><br>All accepted papers will be published by ACM and will be available via the<br>ACM Digital Library. At least one author of each accepted paper must register<br>for the conference and present the paper there.<br><br>AUTHORS TAKE NOTE: The official publication date is the date the<br>proceedings are made available in the ACM Digital Library. This date may be<br>up to two weeks prior to the first day of your conference. The official<br>publication date affects the deadline for any patent filings related to<br>published work. (For those rare conferences whose proceedings are<br>published in the ACM Digital Library after the conference is over, the official<br>publication date remains the first day of the conference.)<br><br><br><b><u>IMPORTANT DATES<br></u></b><br>• Abstract: January 25, 2019 (mandatory)<br><br>• Full paper: February 1, 2019<br><br>• Notification: March 11, 2019<br><br>• Camera-ready: April 3, 2019<br><br>• Adjunct proceedings, camera ready: April 15, 2018<br><br><u>Note</u>: The submissions times are 11:59pm AoE time (Anywhere on Earth).<br><br><br><b><u>GENERAL CHAIRS<br></u></b><br>• George A. Papadopoulos, University of Cyprus, Cyprus<br><br>• George Samaras, University of Cyprus, Cyprus<br><br>• Stephan Weibelzahl, PFH Private University of Applied Sciences,<br>Göttingen, Germany <br><br><br><b><u>RELATED EVENTS<br></u></b><br>Separate calls will be later sent for Workshops and Tutorials, Doctoral<br>Consortium, Demos, Late Breaking Results and Theory, Opinion and<br>Reflection works, as they have different deadlines and submission<br>requirements.<br></font>
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