Intelligent Product Recommendation Framework Using AI in a .NET-Based E-Commerce Architecture

This paper presented BuyWise, an intelligent hybrid product recommendation framework integrated with a .NET-based e-commerce architecture. The proposed system combines collaborative filtering and content-based filtering to generate personalized product recommendations. The architecture uses Angular for the frontend, ASP.NET Core Web API for backend services, MySQL for data storage, and Python Scikit-learn for the ML recommendation engine. Experimental evaluation on a synthetic prototype dataset showed that the hybrid model outperformed standalone approaches in precision, recall, F1 score, and catalogue coverage. The study demonstrates that AI-based recommendation techniques can be practically integrated into full-stack .NET applications and can be extended further for real-world e-commerce deployment.

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