RecSys 2010 Call For Papers

ACM Recommender Systems 2010
Barcelona :: September 26-30, 2010
Call For Papers
CALL FOR PAPERS, PRESENTATIONS, AND DEMOS

We are pleased to invite you to participate in the premier annual event on research and applications of recommendation technologies, the Fourth ACM Conference on Recommender Systems. The previous conferences in Minneapolis, Lausanne and New York have been distinguished by a strong level of interaction between practitioners and researchers in the sharing of ideas, problems and solutions, and the 2010 conference will continue in this tradition. The fully-refereed proceedings will be published by the ACM and, like past RecSys proceedings, are expected to be widely read and cited.
PAPER FORMAT & SUBMISSION

There are three categories of submissions: long papers, short papers, and video presentations.

LONG PAPER submissions should report on substantial contributions of lasting value. Each accepted long paper will be presented in a plenary session of the main conference program. The maximum length is 8 pages in the standard ACM SIG proceedings format. We expect the review process to be highly selective: in 2009, the acceptance rate for full papers was 19%. Deadline: April 16 abstracts, April 23 papers.

SHORT PAPER submissions typically discuss exciting new work that is not yet mature enough for a long paper. Each accepted short paper will be presented in a poster session. That presentation may include a system demonstration. The maximum length is 4 pages in the standard ACM SIG proceedings format. We expect the review process to be much less selective than for full papers, but will still screen for relevance to the conference audience and clarity of presentation. Deadline: April 16 abstracts, April 23 papers.

VIDEO PRESENTATION submissions contain case study reports and demonstrations of intriguing systems. They may include interviews with key players, visuals with voice over, or other creative uses of the video format. This is an opportunity to report using a non-academic communication style. Industry practitioners are especially encouraged to submit. Accepted video presentations will be presented in a poster/demo session and made available via the RecSys’10 homepage. Acceptable file formats are .avi, .movm .mpeg or .wmf. Submissions should contain a weblink to the file. The maximum duration is 10 minutes. Deadline: July 1.

All submissions will be handled electronically by the easychair system. Paper submission will be in PDF format. RecSys10 submissions should be prepared according to the standard ACM SIG proceedings format. For your convenience, we provide paper templates in Microsoft Word and LaTeX on the conference website. RecSys ‘10 will not use double blind review, so please include authors’ names and affiliations on your submission.
AWARDS

The conference will present the Best Paper and the Best Poster award, with the Best Poster award being judged on both the (short) paper itself and on the presentation of the work in poster form.
IMPORTANT DATES

1. Deadline for abstracts (mandatory for long/short papers): April 16, 11.59 pm (PST)
2. Deadline for papers (long/short): April 23, 11.59 pm (PST)
3. Paper Acceptance Notifications: June 23, 2010
4. Deadline for video reports: July 1, 2010
5. Camera-ready copy: July 21, 2010
6. Conference: September 26-30, 2010

TOPICS OF INTEREST

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 case-based reasoning. Topics of interest include (but are not limited to):

* Case studies of recommender system implementations
* Computational advertising
* Conversational recommender systems
* Context-aware and multidimensional recommender systems
* Evaluation of recommender systems
* Group recommenders
* Impact of recommenders in practice
* Innovative recommender applications
* Machine learning and recommender systems
* Novel paradigms of recommender systems
* Personalization
* Recommendation algorithms
* Recommendation in social networks
* Recommender system interfaces
* Scalability issues
* Security, privacy, and robustness
* Semantic web technologies for recommender systems
* Theoretical aspects of recommender systems
* User modeling and recommender systems
* User studies