Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
Proceedings of the 6th international conference on Intelligent user interfaces
Machine Learning
SoNARS: A Social Networks-Based Algorithm for Social Recommender Systems
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
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Users of Social Networking Sites (SNSs) like Facebook, MySpace, LinkedIn, or Twitter, are often overwhelmed by the huge amount of social data (friends' updates and other activities). We propose using machine learning techniques to learn preferences of users and generate personalized recommendations. We apply four different machine learning techniques on previously rated activities and friends to generate personalized recommendations for activities that may be interesting to each user. We also use different non-textual and textual features to represent activities. The evaluation results show that good performance can be achieved when both non-textual and textual features are used, thus helping users deal with cognitive overload.