Conference Information
RecSys 2020: ACM Conference on Recommender Systems
Submission Date:
2020-05-25 Extended
Notification Date:
Conference Date:
Rio de Janeiro, Brazil
CORE: b   QUALIS: b1   Viewed: 17600   Tracked: 42   Attend: 2

Conference Location
Call For Papers
We are pleased to invite you to contribute to the 14th ACM Conference on Recommender Systems (RecSys 2020), the premier venue for research and applications of recommendation technologies. The upcoming RecSys conference will be held in Rio de Janeiro, Brazil, from September 22nd to September 26th, 2020. The conference will continue RecSys’ practice of connecting the research and practitioner communities to exchange ideas, frame problems, and share solutions. All accepted papers will be published by ACM.

We invite submissions on all aspects of recommender systems, including applications ranging from e-commerce to social networking, and a wide variety of technologies ranging from collaborative filtering to knowledge-based reasoning or deep learning. We welcome new research on recommendation technologies coming from very diverse communities ranging from psychology to mathematics. In particular, we care as much about the human and economic impact of these systems as we care about their underlying algorithms.

Topics of interest for RecSys 2020 include but are not limited to (alphabetically ordered):

    Algorithm scalability, performance, and implementations
    Bias, fairness, bubbles and ethics of recommender systems
    Case studies of real-world implementations
    Context-aware recommender systems
    Conversational recommender systems (e.g., conversational interaction, spoken language interfaces, dialogue systems)
    Cross-domain recommendation
    Economic models and consequences of recommender systems
    Evaluation metrics and studies
    Explanations and evidence
    Innovative/New applications
    Interfaces for recommender systems
    Novel machine learning approaches to recommendation algorithms
    Preference elicitation
    Privacy and security
    Social recommenders
    User modelling
    User studies
    Voice, VR, and other novel interaction paradigms

Authors will be asked to assign a selection of predefined custom tags to describe their paper in the submission system. Tags can be assigned to indicate algorithms, interfaces, automated or user-centric evaluations, for example. Reviewers will also report their expertise over these tags, and the information will be used in review assignments.
Last updated by Dou Sun in 2020-04-25
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