526.526. Knowledge Graph Recommendations

### Problem: Knowledge Graph Recommendations

In this problem, we will implement a knowledge graph-based recommendation system using deep learning. The goal is to predict the next item that a user will interact with based on their past interactions and the relationships between items in the knowledge graph.

**Example:** Suppose we have a knowledge graph where items are represented as nodes and relationships between items are represented as edges. Our model should predict that the user will interact with item 6 next, given that they have interacted with items 1, 2, and 3 in the past and that item 6 is related to item 5, which is related to item 4, which is related to item 3.

**Constraints:** The input will be a list of user interactions, where each interaction is a list of item IDs. The output will be a list of item IDs that the user is likely to interact with next. The model should be able to handle knowledge graphs of varying sizes and should be able to learn from the relationships between items.