ACM UMAP 2019 - 27th ACM International Conference on User Modeling, Adaptation and Personalization
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Website https://www.um.org/umap2019/ |
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Category Personalized Recommender Systems; Adaptive Hypermedia And The Semantic Web; Intelligent User Interfaces; Personalized Social Web; Technology-Enhanced Adaptive Learning; Privacy And Fairness; Personalized Music Access; Personalized Health
Deadline: January 25, 2019 | Date: June 09, 2019-June 12, 2019
Venue/Country: Golden Bay Beach Hotel 5*, Larnaca, Cyprus
Updated: 2018-09-20 22:10:03 (GMT+9)
Call For Papers - CFP
*** CALL FOR PAPERS *** 27th ACM International Conference on User Modeling, Adaptationand Personalization (ACM UMAP 2019)Golden Bay Beach Hotel 5*, Larnaca, Cyprus, June 9-12, 2019https://www.um.org/umap2019/Abstracts due: January 25, 2019 (mandatory)Papers due: February 1, 2019BACKGROUND AND SCOPEACM UMAP, "User Modeling, Adaptation and Personalization", is the premierinternational conference for researchers and practitioners working onsystems that adapt to individual users, to groups of users, and that collect,represent, and model user information. ACM UMAP is sponsored by ACMSIGCHI and SIGWEB. The proceedings are published by ACM and will be partof the ACM Digital Library.ACM UMAP covers a wide variety of research areas where personalizationand adaptation may be applied. This include (but is in no way limited to) anumber of domains in which researchers are engendering significantinnovations based on advances in user modeling and adaptation,recommender systems, adaptive educational systems, intelligent userinterfaces, e-commerce, advertising, digital humanities, social networks,personalized health, entertainment, and many more. This year the conference hosts three new tracks, one on privacy andfairness, one on personalized music access, and one on personalized health.CONFERENCE TRACKSTrack 1 - Personalized Recommender SystemsChairs:Marko Tkalcic, Free University of Bozen-Bolzano, marko.tkalcicunibz.itAlan Said, University of Skövde, alansaidacm.orgPersonalized, computer-generated recommendations have become apervasive feature of today’s online world. The underlying recommendersystems are designed to help users and providers in a number of ways.From a user’s viewpoint, for example, these systems assist consumers infinding relevant things within large item collections. On the other hand,from a provider’s perspective, recommenders have also shown to bevaluable tools to steer consumer behavior. From a technical perspective,the design of such systems requires the careful consideration of variousaspects, including the choice of the user modeling approach, the underlyingrecommendation algorithm, and the user interface. This track aims to providea forum for researchers and practitioners to discuss open challenges, latestsolutions and novel research approaches in the field of recommendersystems. Besides the above-mentioned technical aspects, works are alsoparticularly welcome that address questions related to the user perceptionand the business value of recommender systems.Topics include (but are not limited to):• Recommendation algorithms• Recommender and personalization system evaluation• User modeling and preference elicitation• Users’ perception of recommender systems• Business value of recommendation systems and multi-stakeholderenvironments• Explanations and trust• Context-aware recommendation algorithms• Recommending to groups of users• Case studies of real-world implementations• Novel, Psychology-informed User- and Item-modelingTrack 2 - Adaptive Hypermedia And The Semantic WebChairs:Liliana Ardissono, University of Torino, liliana.ardissonounito.itKatrien Verbert, KU Leuven, katrien.verbertcs.kuleuven.beAdaptive hypermedia and adaptive web explore alternatives to the traditional“one-size-fits-all” approach in the development of web and hypermediasystems. Adaptive hypermedia and adaptive web systems build a model ofthe interests, preferences and knowledge of each individual user, and usethis model in order to adapt the behavior of hypermedia and web systems tothe needs of that user. Semantic web frequently serves as an infrastructureto enable adaptive and personalized Web systems. Semantic web technologytargets the use of explicit semantics and metadata to help web systemsperform the desired functionality: this implies the use of linked data fromthe web, the use of ontologies in models, or the use of metadata in userinterfaces, as well as the use of ontologies for information integration. Thistrack aims to provide a forum to researchers to discuss open researchproblems, solid solutions, latest challenges, novel applications and innovativeresearch approaches in adaptive hypermedia and semantic web.Topics include (but are not limited to):• Web user profiles• Adaptive navigation support• Personalized search• Web content adaptation• Analytics of web user data• Adaptive web sites and portals• Adaptive books and textbooks• Social navigation and social search• Navigation support in continuous media and virtual environments• Usability engineering for adaptive hypermedia and web systems• Novel methodologies for evaluating adaptive hypermedia and web systems• Semantic Web technologies for web personalization• Ontology-based data access and integration/exchange on the adaptive web• Ontology engineering and ontology patterns for the adaptive web• Ontology-based user models• Semantic social network mining, analysis, representation, and management• Crowdsourcing semantics; methods, dynamics, and challenges• Semantic Web and Linked Data for adaptationTrack 3 - Intelligent User InterfacesChairs:Li Chen, Hong Kong Baptist University, lichencomp.hkbu.edu.hkJingtao Wang, Google, jingtaowacm.org Intelligent User Interfaces aim to improve the interaction between computersystems and human users by means of Artificial Intelligence. The systemssupport and complement different types of abilities that are normallyunavailable in the context of human-only cognition. Previous work has foundthat humans do not always make the best possible decisions when workingtogether with computer systems. By designing and deploying improved formsof support for interactive collaboration between human decision makers andsystems, we can enable decision making processes that better leverage thestrengths of both collaborators. More generally this research track can becharacterized by exploring how to make the interaction between computersand people smarter and more productive, which may leverage solutions fromhuman-computer interaction, data mining, natural language processing, information visualization, and knowledge representation and reasoning.Topics include (but are not limited to):• Adaptive personal virtual assistants (e.g., interaction with robots)• Adapting natural interaction (e.g., natural language, speech, gesture)• Intelligent user interfaces based on sensor data (UIs for cars, fridges, etc.)• Multi-modal interfaces (speech, gestures, eye gaze, face, physiological info, etc.)• Intelligent wearable and mobile interfaces• Smart environments and tangible computing• Transparency and control of decision support systems(e.g., semi-autonomous systems)• Explainable intelligent user interfaces• Affective and aesthetic interfaces• Tailored persuasion and argumentation interfaces• Tailored decision support (e.g., over- and under-reliance in uncertaindomains)• Adaptive information visualization• Scalability of intelligent user interfaces to access huge datasets• User-centric studies of interactions with intelligent user interfaces• Novel datasets and use cases for intelligent user interfaces• Evaluations of intelligent user interfacesTrack 4 - Personalized Social WebChairs:Ilaria Torre, University of Genova, ilaria.torreunige.itOsnat Mokryn, omokrynuniv.haifa.ac.ilThe social web is continuously growing and social platforms are afundamental part of our life. Mediated communication is becoming theprimary form of communication for young people, and adults follow inincreasing numbers. Online communication is increasingly enriched by theuse 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 personalinformation source, gathered for private use through personal devices, is nowoften shared in online communities. These trends open new challenges forresearch: how to harness the power of collective intelligence and quantifiedself data in online social platforms to identify social identities, how to exploitcontinuous feedback threads, and how to improve the individual userexperience on the social web. We invite original submissions addressing all aspects of personalization,user models building and personal experience in online social systems.Topics include (but are not limited to):• Personalization of the web experience in social systems• Adaptations based on personality, society, and culture• Personalization algorithms and protocols inspired by human societies• Social recommendation• Identifying social identities in social media• Social and crowd-generated data for adaptation• Personalized information retrieval• Exploiting quantified self data on the social web of things• Data-driven approaches for personalization• Modeling individuals, groups, and communities• Collective intelligence and experience mining• Pattern and behaviour discovery in social network analysis• Opinion mining for user modeling• Sentiment analysis• Topic modeling for online conversations and short texts• Privacy, perceived security, and trust in social systems• Ethical issues involved in studying the social web• User awareness and control• Evaluation methodologies for the social webTrack 5 - Technology-Enhanced Adaptive LearningChairs:Jesús G. Boticario, UNED, jgbdia.uned.esInge Molenaar, Radboud University, i.molenaarpwo.ru.nlAt large there is an on-going “fusion” between humans and technologicalsystems. The ongoing integration of devices into our daily lives furthers theintegration of technology in human learning. With technology increasinglygaining more data and intelligence, a new era of technology-enhancedadaptive learning is emerging. Consequently, the interactions betweenlearners, 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 whichinteract with the learning context. Smart technological solutions areincreasingly able to identify and model the learner needs on these fiveaspects and accordingly provide personalized support that can improve theeffectiveness, efficiency and satisfaction of learning experiences.Current research in artificial intelligence combined with data science andlearning analytics bring new opportunities to recognize, and effectivelysupport individual learners’ needs and orchestrate collaborate andclassroom learning with intelligent learning solutions, and augment teachersin blended learning situations. The aim of this track is to foreground thesystematic complexity of human learning and use systematic analyticapproaches to measure, diagnose and support human learning withtechnologies. This covers not only formal educational settings, but alsolifelong learning requirements (including workplace training) as well as theacquisition of skills informal learning settings (e.g., in daily activities, seriousgames, sports, healthcare, wellbeing, etc.).To address the wide spectrum of modeling issues and challenges that can beraised, contributions from various research areas are welcome. Therefore,this track invites researchers, developers, and practitioners from variousdisciplines to present their innovative adaptive learning solutions, shareacquired experience, and discuss the main modeling challenges fortechnology enhanced adaptive learning.Topics include (but are not limited to):• Domain, learner, teacher and context modeling• Modeling cognitive, metacognitive, motivational, affective and psychomotoraspects of learning• Diagnosis of learner needs and calibration of support and feedbackAdaptive and personalized support for learning• 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• Management of large, open, and public datasets for educational data mining• Agent-based learning environments and virtual pedagogical agents• Open corpus personalized learning• Collaborative and group learning• Adaptive technologies to orchestrated classroom Learning• Personalized teachers awareness and support tools• Multimodal learning analytics to personalize learning• UMAP aspects in specific learning solutions: educational recommendersystems, intelligent tutoring systems, serious games, personal learningenvironments, MOOCs• Wearable technologies and augmented reality in adaptive personalizedlearning• Processing collected data for UMAP: educational data mining, learninganalytics, big data, deep learning.• Semantic web and ontologies for e-learning• Interoperability, portability, and scalability issues• Case studies in real-world educational settings• New methodologies to develop user-centered highly personalized learningsolutionsTrack 6 - Privacy And FairnessChairs:Bart Knijnenburg, Clemson University, bartkclemson.eduEsma Aimeur, University of Montreal, aimeuriro.umontreal.caAdaptive systems researchers and developers have a social responsibility tocare about their users. This involves building, maintaining, evaluating, andstudying adaptive systems that are fair, transparent, and protect users'privacy. We invite papers that study, in the context of UMAP, the topics ofprivacy (as well as innovative means to resolve privacy problems throughalgorithms, interfaces, or other technical or non-technical means), fairness(covering the spectrum from algorithmic fairness to social implications ofadaptive systems), and transparency (as a concept of system usability aswell as a means to resolve problems with privacy and fairness). Beyond thiswe encourage authors to submit to this track any work that ascribes to oradvances the general idea of "adaptive systems that care”.Privacy topics:• Analysis of privacy implications of user modeling• Privacy compliance• Algorithmic solutions to privacy• Architectural solutions to privacy• Interactive solutions to privacy• Usable privacy for adaptive systems• User perceptions of privacy in UMAP applications• Studies of users’ privacy-related behaviors in UMAP applications• Descriptions or evaluations of privacy-settings user interfaces• Privacy prediction / personalization• User-tailored approaches to privacy• Privacy education for user modeling• Modeling of data protection and privacy requirements• Economics of privacy and personal data• Measuring privacyFairness topics:• Ethical considerations for user modeling• UMAP applications for underrepresented groups• Cultural differences (e.g. culture-aware user modeling)• Bias and discrimination in user modeling• Imbalance in meeting the needs of different groups of users• Balancing needs of users versus system owners• Ethics of explore/exploit strategies or A/B testing• ‘Filter bubble’ or ‘balkanization’ effects• Enhancing/embracing diversity in user modeling• Algorithmic methods for increasing fairness• User perceptions of fairness• Measuring fairnessTransparency topics:• User perceptions of transparency• Transparent algorithms• Interface innovations that increase transparency• Explanations for transparency• Visualizations for transparency• Adaptive systems for self-actualization• (User-centric) evaluations of methods that increase transparency• Measuring transparencyTrack 7 - Personalized Music AccessChairs:Markus Schedl, University of Linz, markus.schedljku.atNava Tintarev, TU Delft, n.tintarevtudelft.nlMusic access systems (e.g., search, retrieval, and recommendation systems)have experienced a boom during the past decade due to the availability ofhuge music catalogs to users, anywhere and anytime. These systems recordinformation on user behavior in terms of actions on music items, such asplay, skip, or playlist creation and modification. As a result, an abundance ofuser and usage data has been collected and is available to companies andacademics, allowing for user profiling and to create and improve personalizedmusic access. This track addresses unsolved challenges in this area relatingto user understanding and modeling, personalization in recommendation andretrieval systems, modeling usage context, and adapting interactiveintelligent music interfaces. This track aims to provide a forum forresearchers and practitioners for the latest research on? user modeling andpersonalization for finding, making, and interacting with music.Topics include (but are not limited to):• Personalized music preference elicitation and preference learning• Psychological modeling of music listeners (e.g., personality, emotion, etc.)• Subjective perceptions of music (e.g., similarity, mood, tempo) social andcultural aspects of listening behavior (e.g., for group recommenders)• Applications for personalized music consumption and creation• Personalized playlist generation and continuation (e.g., sequences andtransitions)• Personalized music interaction and interface paradigms (e.g., visualization,VR)• Explainability, transparency, and fairness in personalized music• Systems user-centric performance measures (e.g., diversity, novelty,serendipity, etc.)• Datasets (including benchmarks) for personalizing music retrieval andrecommendationTrack 8 - Personalized HealthChairs:Christoph Trattner, University of Bergen, trattner.christophgmail.comDavid Elsweiler, University of Regensburg, davidelsweiler.co.ukGrowing health issues and rising treatment costs mean that technologicalsystems are increasingly important for global health. Personalised systems,tailored to the needs and behaviours of individual patients, are one of thepromising approaches to health promotion by encouraging lifestyle change,managing treatment programmes and providing doctors and otherhealthcare providers with detailed individualized feedback. The challenges todeveloping such systems, which model user needs and preferences, as well asappropriate medical knowledge to provide assistance and recommendationsare plentiful. The diverse technologies which could potentially feature insolutions are equally vast, ranging from AI systems to sensors, from mobilecomputing, augmented reality and visualization, to mining the web or otherdata streams to learn about health issues and user behaviour. In this track weinvite scholars working in these or related areas to contribute to the discourseon how technology can promote health. This track aims to provide a forum toresearchers to discuss open research problems, solid solutions, latestchallenges, novel applications and innovative research approaches and indoing so to strengthen the community of researchers working onPersonalized Health and attract representatives from from diverse scholarlybackgrounds ranging from computer and information science to publichealth, epidemiology, psychology, medicine, nutrition and fitness.Topics include (but are not limited to):• Algorithms and Recommendation Strategies to increase health• Mobile health• Quantified self• Applied data analytics and modeling for health• Health risk modeling and forecasting• Systems for Preventative Measures• Medical Evaluation Techniques• Domain Knowledge Representation• Behavioral Interventions: Persuasion/Nudging/Behavioral Change• HCI, Interfaces and Visualisations for health• Regulations and Standards• Human/ Expert-in-the-Loop• Gamification and Serious Games• Privacy, Trust, Ethics• DatasetsSUBMISSION AND REVIEW PROCESSPapers should be submitted through EasyChair:https://easychair.org/conferences/?conf=acmumap2019The ACM User Modeling, Adaptation, and Personalization (ACM UMAP) 2019Conference will include high quality peer-reviewed papers related to theabove key areas. Maintaining the high quality and impact of the ACM UMAPseries, each paper will have three reviews by program committee membersand a meta-review presenting the reviewers’ consensual view; the reviewprocess will be coordinated by the program chairs in collaboration with thecorresponding area chairs.Long (8 pages + references) and Short (4 pages + references) papers in ACMstyle, peer reviewed, original, and principled research papers addressing boththe theory and practice of UMAP and papers showcasing innovative use ofUMAP and exploring the benefits and challenges of applying UMAPtechnology in real-life applications and contexts are welcome.Long papers should present original reports of substantive new researchtechniques, findings, and applications of UMAP. They should place the workwithin the field and clearly indicate innovative aspects. Research proceduresand technical methods should be presented in sufficient detail to ensurescrutiny and reproducibility. Results should be clearly communicated andimplications of the contributions/findings for UMAP and beyond should beexplicitly discussed.Short papers should present original and highly promising research orapplications. Merit will be assessed in terms of originality and importancerather than maturity, extensive technical validation, and user studies.Separation of long and short papers will be strictly enforced so papers willnot compete across categories, but only within each category. Papers thatreceive high scores and are considered promising by reviewers, but didn’tmake the acceptance cut, will be directed to the poster session of theconference and will be invited to be resubmitted as posters.Papers must be formatted using the ACM SIG Standard (SIGCONF) proceedingstemplate: https://www.acm.org/publications/proceedings-template .Please note that ACM changed its templates at the start of 2017, so pleaseensure 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 theACM Digital Library. At least one author of each accepted paper must registerfor the conference and present the paper there.AUTHORS TAKE NOTE: The official publication date is the date theproceedings are made available in the ACM Digital Library. This date may beup to two weeks prior to the first day of your conference. The officialpublication date affects the deadline for any patent filings related topublished work. (For those rare conferences whose proceedings arepublished in the ACM Digital Library after the conference is over, the officialpublication date remains the first day of the conference.)IMPORTANT DATES• Abstract: January 25, 2019 (mandatory)• Full paper: February 1, 2019• Notification: March 11, 2019• Camera-ready: April 3, 2019• Adjunct proceedings, camera ready: April 15, 2018Note: The submissions times are 11:59pm AoE time (Anywhere on Earth)GENERAL CHAIRS• George A. Papadopoulos, University of Cyprus, Cyprus• George Samaras, University of Cyprus, Cyprus• Stephan Weibelzahl, PFH Private University of Applied Sciences,Göttingen, Germany RELATED EVENTSSeparate calls will be later sent for Workshops and Tutorials, DoctoralConsortium, Posters, Late Breaking Results and Theory, Opinion andReflection works, as they have different deadlines and submissionrequirements.
Keywords: Accepted papers list. Acceptance Rate. EI Compendex. Engineering Index. ISTP index. ISI index. Impact Factor.
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