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RecSys 2012 : ACM International Conference on Recommender Systems (RecSys) 2012

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Conference Series : Conference on Recommender Systems
 
Link: http://recsys.acm.org/2012/
 
When Sep 9, 2012 - Sep 13, 2012
Where Dublin, Ireland
Abstract Registration Due Apr 2, 2012
Submission Deadline Apr 9, 2012
Notification Due Jun 1, 2012
Final Version Due Jun 22, 2012
 

Call For Papers

Final Call for Papers

We are pleased to invite you to participate in the premier annual event on research and applications of recommendation technologies, the Sixth ACM Conference on Recommender Systems (RecSys 2012). The previous conferences have been distinguished by a strong level of interaction between researchers and practitioners in the sharing of ideas, problems and solutions, and the 2012 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.
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 for RecSys 2012 include (but are not limited to):

Algorithm scalability
Case studies of real-world implementations
Computational advertising
Conversational recommender systems
Context-aware and multidimensional models
Evaluation metrics and studies
Explanations and evidence
Group recommenders
Impact studies
Innovative/New applications
Machine learning for recommendation
Novel paradigms
Personalization
Preference elicitation
Recommendation algorithms
Social recommenders
User interfaces
Security, privacy, trust, and reputation
Semantic web technologies for recommendation
Theoretical foundations
User modelling
User studies

Paper Format and Submission

All submissions and reviews will be handled electronically in PDF format. RecSys 2012 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. More details on the submission procedure are available here.

There are two paper submission categories:

Long paper submissions should report on substantial contributions of lasting value. The maximum length is 8 pages in the standard ACM SIG proceedings format. Each accepted long paper will be presented in a plenary session as part of the main conference program. We expect the review process to be highly selective: in 2011, the acceptance rate for full papers was 20%.
Short paper submissions typically discuss exciting new work that is not yet mature enough for a long paper. The maximum length is 4 pages in the standard ACM SIG proceedings format. Each accepted short paper will be presented in a poster session. The presentation may include a system demonstration.

Note: Please note that rejected long paper submissions will not be automatically considered as short papers.
Awards

As in previous years Best Paper and the Best Poster awards will be presented as part of the conference main social event.

Related Resources

RecSys 2019   13th ACM Conference on Recommender Systems
RecSys@FLAIRS 2020   Recommender Systems Track at FLAIRS Conference
UMAP 2020   ACM International Conference on User Modeling, Adaptation and Personalization
Recommender Systems 2020   Data Science for Next-Generation Recommender Systems
SIGSPATIAL 2020   28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
ORSUM 2019   2nd Workshop on Online Recommender Systems and User Modeling @ ACM RecSys 2019
ACM--NLPIR--Ei Compendex and Scopus 2020   ACM--2020 4th International Conference on Natural Language Processing and Information Retrieval (NLPIR 2020)--Scopus, Ei Compendex
RecNLP 2019   The AAAI 2019 Workshop on Recommender Systems and Natural Language Processing
ACM--ICMLT--Ei and Scopus 2020   ACM--2020 5th International Conference on Machine Learning Technologies (ICMLT 2020)--Ei Compendex, Scopus
UMUAI FatRec 2019   UMUAI Special issue on: Fair, Accountable, and Transparent Recommender Systems