Over-Fitting and Error Detection for Online Role Mining
International Journal of Web Services Research
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Finding and recommending suitable services for moving, connected devices are increasingly important due to the popularity of mobile Internet. While recent research has attempted to use role-based approaches to recommend services, role discovery is still an ongoing research topic. This paper proposes a simple and yet efficient, matrix-based, context-aware role mining method to automatically group users according to their interests and habits. Using a question-based approach, we also allow popular mobile services to be recommended to other members in the same group in a context dependent.