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UMAP 2019: International Conference on User Modeling, Adaptation, and Personalization - Call for paper, ranking, acceptance rate, submission deadline, notification date, conference location, submission guidelines, and other important details


This article provides the call for paper, ranking, acceptance rate, submission deadline, notification date, conference location, submission guidelines, and other important details of UMAP 2019: International Conference on User Modeling, Adaptation, and Personalization all at one place.

Conference Location Larnaca, Cyprus
Conference Date 2019-06-09
Notification Date 2019-03-11
Submission Deadline 2019-01-25
Conference Website and Submission Link http://www.cyprusconferences.org/umap2019/


Conference Ranking


International Conference on User Modeling, Adaptation, and Personalization ranking based on CCF, Core, and Qualis is shown below:

CCF Ranking
Core Ranking B
Qualis Ranking B1

Click here to check the ranking of any conference.
  • About CCF Ranking: The Chinese Computing Federation (CCF) Ranking provides a ranking of peer-reviewed journals and conferences in the field of computer science.

  • About Core Ranking: The CORE Conference Ranking is a measure to assess the major conference in the computing field. This ranking is governed by the CORE Executive Committee. To know more about Core ranking, visit Core ranking portal.

  • About Qualis Ranking: This conference ranking is published by the Brazilian ministry of education. It uses the h-index as a performance metric to rank conferences. Conferences are classified into performance groups that range from A1 (to the best), A2, B1, B2,..., B5 (to the wost). To know more about qualis ranking, visit here

Conference Acceptance Rate


Below is the acceptance rate of International Conference on User Modeling, Adaptation, and Personalization conference for the last few years:

Year Submitted Papers Accepted Papers Accepted Percentage/Acceptance Rate

We are working hard to collect and update the acceptance rate details of the conferences for recent years. However, you can consider the above (if available) acceptance rates to predict the average chances of acceptance of your research paper at this conference.



Conference Call for paper


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.Conference TracksTrack 1 - Personalized Recommender SystemsChairs:Marko Tkalcic, Free University of Bozen-Bolzano, [email protected] Said, University of Skövde, [email protected], 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):
Recommendation algorithms
Recommender and personalization system evaluation
User modeling and preference elicitation
Users’ perception of recommender systems
Business value of recommendation systems and multi-stakeholder environments
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, [email protected] Verbert, KU Leuven, [email protected] 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.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, [email protected] Wang, Google, [email protected] 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.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 uncertain domains)
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, [email protected] Mokryn, [email protected] 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.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, [email protected] Molenaar, Radboud University, [email protected] 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.Topics include (but are not limited to):
Domain, learner, teacher and context modeling
Modeling cognitive, metacognitive, motivational, affective and psychomotor aspects of learning
Diagnosis of learner needs and calibration of support and feedback Adaptive and personalized support for learning
Dealing with ethical issues involved in detecting and modeling a wider range of information sources (e.g., information from novel sensing devices, 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 recommender systems, intelligent tutoring systems, serious games, personal learning environments, MOOCs
Wearable technologies and augmented reality in adaptive personalized learning
Processing collected data for UMAP: educational data mining, learning analytics, 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 learning solutionsTrack 6 - Privacy and FairnessChairs:Bart Knijnenburg, Clemson University, [email protected] Aimeur, University of Montreal, [email protected] 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”.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, [email protected] Tintarev, TU Delft, [email protected] 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.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 and cultural aspects of listening behavior (e.g., for group recommenders)
Applications for personalized music consumption and creation
Personalized playlist generation and continuation (e.g., sequences and transitions)
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 and recommendationTrack 8 - Personalized HealthChairs:Christoph Trattner, University of Bergen, [email protected] Elsweiler, University of Regensburg, [email protected] 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.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) 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

Submission Deadline


UMAP 2019: International Conference on User Modeling, Adaptation, and Personalization submission deadline is 2019-01-25.

Note: It is generally recommended to submit your conference paper on or before the submission deadline. Generally, conferences do not encourage to submit the research paper after the deadline is over. In rare scenarios, conferences extend their deadline. Decision about the extension of the deadline is generally updated on the official conference webpage.


Notification date


Notification date of UMAP 2019: International Conference on User Modeling, Adaptation, and Personalization is 2019-03-11.

Note: This is the date on which conference announces the result about acceptance or rejection of submitted papers. If your research paper is accepted, the conference will request you to submit the camera ready version of your research paper by the due date. Due date to submit the camera ready version of the paper is generally posted on the official web page of the conferences or notified to you via. email.


Conference Date


UMAP 2019: International Conference on User Modeling, Adaptation, and Personalization will start on 2019-06-09.

Note: This is the date on which the conference starts.


Conference Location


UMAP 2019: International Conference on User Modeling, Adaptation, and Personalization will be organized at Larnaca, Cyprus. This is the place where the conference is organized and the research paper is to be presented.