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活动简介

The ACM Recommender Systems conference (RecSys) is the premier international forum for the presentation of new research results, systems and techniques in the broad field of recommender systems. Recommendation is a particular form of information filtering, that exploits past behaviors and user similarities to generate a list of information items that is personally tailored to an end-user’s preferences. As RecSys brings together the main international research groups working on recommender systems, along with many of the world’s leading e-commerce companies, it has become the most important annual conference for the presentation and discussion of recommender systems research. RecSys 2016, the tenth conference in this series, will be held in Boston, MA, USA. It will bring together researchers and practitioners from academia and industry to present their latest results and identify new trends and challenges in providing recommendation components in a range of innovative application contexts. In addition to the main technical track, RecSys 2016 program will feature keynote and invited talks, tutorials covering state-of-the-art in this domain, a workshop program, an industrial track and a doctoral symposium. Published papers will go through a rigorous full peer review process. The conference proceedings, which will be available both on a USB drive and via the ACM Digital Library, are expected to be widely read and cited. ACM RecSys 2016 will take place at the Massachusetts Institute of Technology (MIT) and the IBM Research campuses from September 15-19, 2016.

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Topics of interest for RecSys 2016 include (but are not limited to):

  • Algorithm scalability
  • Case studies of real-world implementations
  • Conversational recommender systems
  • Context-aware recommenders
  • Evaluation metrics and studies
  • Explanations and evidence
  • Field and user studies
  • Group recommenders
  • Impact studies
  • Innovative/New applications
  • Machine learning for recommendation
  • Mobile and multi-channel recommendations
  • Novel paradigms
  • Personalization
  • Preference elicitation
  • Privacy and Security
  • Recommendation algorithms
  • Social recommenders
  • Semantic technologies for recommendation
  • Targeted advertising
  • Trust and reputation
  • Theoretical foundations
  • User interaction and interfaces
  • User modeling
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重要日期
  • 会议日期

    09月15日

    2016

    09月19日

    2016

  • 09月19日 2016

    注册截止日期

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