What is RecSys?
<br>Recommender systems (RecSys) are being used to suggest products to customers, provide personalized product information, or even to provide products' reviews. These systems recommend items among a huge number of possibilities and according to users' interests. Recommender Systems have also been proposed to support the information selection and decision making processes on e-commerce web sites.
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<br>The development of Recommender Systems represent a multi-disciplinary endeavor involving contributions from various fields of interest for this conference: Artificial Intelligence, Data Mining, Big Data, Human-Computer and Adaptive Interfaces, Information Technology, Statistics, Social Networks, and Consumer Behavior. The scope of recommender systems encompasses algorithmic techniques, applications and evaluation of recommender systems, interacting with recommender systems, recommender systems and communities, and advanced algorithms. [Recommender Systems Handbook...
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What is RecSys?
<br>Recommender systems (RecSys) are being used to suggest products to customers, provide personalized product information, or even to provide products' reviews. These systems recommend items among a huge number of possibilities and according to users' interests. Recommender Systems have also been proposed to support the information selection and decision making processes on e-commerce web sites.
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<br>The development of Recommender Systems represent a multi-disciplinary endeavor involving contributions from various fields of interest for this conference: Artificial Intelligence, Data Mining, Big Data, Human-Computer and Adaptive Interfaces, Information Technology, Statistics, Social Networks, and Consumer Behavior. The scope of recommender systems encompasses algorithmic techniques, applications and evaluation of recommender systems, interacting with recommender systems, recommender systems and communities, and advanced algorithms. [Recommender Systems Handbook; Ricci, F., Rokach, L., Shapira, B., Kantor, P.B., eds.; Springer 2011]
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<br>What is the GOAL of the track?
<br>Provide a forum for researchers and practitioners to share their efforts in addressing current issues, challenges, novel approaches, and applications within the broad scope of recommender systems.
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<br>Who might be interested?
<br>Computer Science and Information Technology researchers and practitioners from academia and industry that are actively involved with Recommender Systems.
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<br>What kind of studies will be of interest?
<br>Papers and contributions are encouraged for any work relating to Recommender Systems. Topics of interest may include (but are in no way limited to):
<br>o Recommendation Algorithms
<br>o Machine Learning for Recommendation
<br>o Multi-Agent Recommender Systems
<br>o Group Recommendations
<br>o Recommendations and Social Networks, Social Recommenders
<br>o Context-aware recommenders
<br>o Preference elicitation
<br>o Personalization
<br>o Trust and Recommendations
<br>o Privacy and Security
<br>o Robustness
<br>o Evaluation metrics and studies
<br>o Novel paradigms (Affective computing, sentiment analysis, ...)
<br>o User modelling
<br>o Recommender system user interfaces
<br>o User studies, online user experiments
<br>o Case studies of real-world implementations
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<br>Note: We invite original papers (i.e. work not previously submitted, in submission, or to be submitted to another conference during the reviewing process).
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<br>Submission Guidelines
<br>Interested authors should format their papers according to AAAI formatting guidelines. The papers should be original work (i.e., not submitted, in submission, or submitted to another conference while in review). Papers should not exceed 6 pages (4 pages for a poster) and are due by November 17, 2014. For FLAIRS-28, the 2015 conference, the reviewing is a double blind process. Fake author names and affiliations must be used on submitted papers to provide double-blind reviewing. Papers must be submitted as PDF through the EasyChair conference system, which can be accessed through the main conference web site (http://www.flairs-28.info/). Note: do not use a fake name for your EasyChair login - your EasyChair account information is hidden from reviewers. Authors should indicate the RecSys special track for submissions. The proceedings of FLAIRS will be published by the AAAI. Authors of accepted papers will be required to sign a form transferring copyright of their contribution to AAAI. FLAIRS requires that there be at least one full author registration per paper.
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<br>Please check the website http://www.flairs-28.info/ for further information.
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<br>Conference Proceedings
<br>Papers will be refereed and all accepted papers will appear in the conference proceedings, which will be published by AAAI Press.
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<br>Further Information
<br>Questions regarding the RecSys Special Track should be addressed to the track co-chairs:
<br>Fabiana Lorenzi, Universidade Luterana do Brasil, florenzi@ulbra.edu.br
<br>Carlos E. Seminario, University of North Carolina at Charlotte, cseminar@uncc.edu
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<br>Conference Web Sites
<br>Paper submission site: follow the link for submissions at http://www.flairs-28.info/
<br>FLAIRS-28 conference web page: http://www.flairs-28.info/
<br>Florida AI Research Society (FLAIRS): http://www.flairs.com
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