Call for Papers

Papers should be submitted through EasyChair.

UMAP 2017 will include high quality peer-reviewed papers related to the above key areas. Maintaining the high quality and impact of the 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 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.

Submission ACM Standard (SIGCONF) templates: http://www.acm.org/publications/proceedings­-template

Intelligent User Interfaces aim to improve the interaction between computational intelligence and human intelligence. Computational intelligence supports different and complementary types of abilities than normally are available in the context of human-only cognition. Some of the previous work has found that humans do not always make the best possible decisions when working together with artificial intelligent systems. By designing and testing improved forms of support for interactive collaboration between human decision makers and artificial advice givers, we can enable decision making processes that better leverage the strengths of both collaborators. More generally the research in track can be characterised by exploring how to make the interaction between computers and people smarter, which may leverage solutions from data mining, natural language processing, novel interaction paradigms, and knowledge representation and reasoning.

Topics include (but are not limited to):

Recommender systems have become essential tools in many application areas as they help alleviate information overload by tailoring their recommendations to users’ personal preferences. They assist users in decision making by providing personalized services and help information providers and companies to more effectively serve customers. The development of recommender systems has led to the emergence of a burgeoning research community spanning a broad range of problems and disciplinary areas. This track aims to provide a dedicated forum to researchers and practitioners to discuss open research problems, solid solutions, latest challenges, novel applications and innovative research approaches in personalized recommendation.

Topics:

Learning is a traditional domain for applying personalization and adaptation technologies. A major aim is to improve effectiveness and efficiency of learning experiences. Technological innovations bring new opportunities how to recognize learner’s needs and how to orchestrate suitable learning solutions. This covers not only formal educational settings, but also lifelong learning requirements, including workplace training. In addition to cognitive aspects of learning, also affective, motivational, and metacognitive ones play an important role. To address the wide spectrum of issues and challenges in this field contributions from various research areas are necessary. Therefore, this track invites researchers, developers, and practitioners from various disciplines to present their innovative solutions, share acquired experience, and discuss main challenges in personalized and adaptive learning.

Topics:

The Social Web has democratized the possibility to produce and consume information by enabling new forms of interaction, collaboration, and mass communication. Individual users are exposed only to a minuscule portion of the unceasing deluge of data that is originated by the collective crowd; as a result, everyone’s experience on the social web is very personal. To better understand and improve the effectiveness of online social systems it is crucial to learn more about the local perception that individuals and groups have of their surroundings and link those perceptions with observable user behavior. Automated personalization tools that can improve the individual user experience are key to drive user engagement and to grow healthier communities.
We invite original submission addressing all aspects of personalization and personal experience in online social systems.

Research topics of interest include, but are not limited to:

Adaptive hypermedia and the 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. 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.

Topics include (but are not limited to):

Page limits: Long papers ­ 8 pages + references; Short pages: 4 pages + references.
Note that the references do not count towards page limits. Papers that exceed the page limits or formatting guidelines will be returned without review.
Submissions should be single blinded, i.e. authors names should be included in the submissions.
Papers must be formatted using the ACM SIG proceedings template: http://www.acm.org/publications/proceedings­-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.

We are pleased to inform that the New Review of Hypermedia and Multimedia journal will feature a special issue on User Modeling, Adaptation and Personalization. During or after the conference, authors of selected UMAP papers will be invited to submit the extended versions of their papers to this special issue.