RecSys 2017 - Eleventh ACM Conference on Recommender Systems

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.
We construe recommender systems broadly, including applications ranging from e-commerce to social networking, platforms from web to mobile and beyond, and a wide variety of technologies ranging from collaborative filtering to knowledge-based reasoning. Topics of interest for RecSys 2017 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 modelling