Adaptive Learning Path Recommendation Engine

Create a graph-based database solution using Neo4j that dynamically generates personalized learning paths for students. Implement advanced traversal algorithms that recommend course progressions based on individual performance, skill gaps, and learning style metrics. Design a recommendation system that can process complex relationship queries with sub-100ms latency and supports real-time path recalculation.