We are pleased to announce the availability of all Calls for Contributions for the 10th ACM Conference on Recommender Systems to be held in Boston, MA, September 15th-19th 2016.
Full details on all calls are available at https://recsys.acm.org/recsys16/call/ Due dates are: - Long and Short Papers: Abstracts Apr. 13, papers Apr. 20 - Tutorials: May 15 - Workshops: Feb. 28 - Doctoral Symposium Papers: May 2 - Demos: Apr. 30 - Posters: July 1 - Industry Talk Proposals: Apr. 13 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-userâs preferences. As RecSys brings together the main international research groups working on recommender systems, along with many of the worldâs 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. -- Michael D. Ekstrand Assistant Professor, Dept. of Computer Science Texas State University
