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 according to users’ interests. Recommender Systems have also been proposed to support the information selection and decision making processes on e-commerce web sites. This is the third Recommender Systems Special Track running in conjunction with the International FLAIRS Conference. The goal of this new special track has been 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. We continue to aim to cover a wide variety of research areas where recommender systems may be researched and applied.
Recommendation Algorithms
Machine Learning for Recommendation
Multi-Agent Recommender Systems
Group Recommendations
Recommendations and Social Networks
Context-aware recommenders
Preference elicitation
Personalization
Trust and Recommendations
Privacy and Security
Robustness
Evaluation metrics and studies
Novel paradigms (Affective computing, sentiment analysis, …)
User modelling
Recommender system user interfaces
Case studies of real-world implementations
05月22日
2017
05月24日
2017
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