There is a critical need for innovative recommendation technology for digital data engineering artifacts and tools. To address this need, we propose design and implement the Artificial Intelligence-based Recommender System for Model-Based Systems Engineering (ARMS) software as a user-personalized context-aware content recommender system solution for Model Based Systems Engineering (MBSE) applications with novel artificial intelligence algorithms. The key innovation is to offer a complete Software-as-a-Service solution that can process multimodal data across different databases, provide high-quality personalized recommendations using novel machine learning techniques. Approved for Public Release | 22-MDA-11339 (13 Dec 22)
