FLAIRS-RS 2015 - Florida Artificial Intelligence Research Society - RecSys Special Track

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. The goal of this new special track is to 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.
Papers and contributions are encouraged for any work relating to Recommender Systems. Topics of interest may include (but are in no way limited to):
o Recommendation Algorithms
o Machine Learning for Recommendation
o Multi-Agent Recommender Systems
o Group Recommendations
o Recommendations and Social Networks, Social Recommenders
o Context-aware recommenders
o Preference elicitation
o Personalization
o Trust and Recommendations
o Privacy and Security
o Robustness
o Evaluation metrics and studies
o Novel paradigms (Affective computing, sentiment analysis, ...)
o User modelling
o Recommender system user interfaces
o User studies, online user experiments
o Case studies of real-world implementations