Cross-Contextual Recommendation Engine Architecture

Develop a sophisticated recommendation system capable of generating personalized, context-aware recommendations by integrating multiple data signals and understanding complex user preferences. Create an architecture that can handle cold-start problems, manage multi-dimensional user representations, and dynamically adapt recommendation strategies. Include advanced techniques for collaborative filtering, transfer learning, and probabilistic preference modeling.