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Modern society is characterized by abundance of data, yet lack of (relevant) information. A major challenge consists in selecting valuable information according to specific criteria. Moreover, ranking it and defining relevance according to the context is decisive. We propose a framework to retrieve content according to context. Our approach relies on a three layers model, each contributing to a better context matching. The implementation has been tuned, and the experiments performed on the Context Match problem.