Schedule
Tutorial Schedule
Detailed Schedule
| Duration | Activity |
|---|---|
| 10 min | Introduction Motivation, limitations of centralized personalization, and overview of PKG-driven decentralization. |
| 30 min | Personal Knowledge Graph Foundations PKG representation, provenance, schema alignment, and examples (FoodKG, Health and Finance PKGs). |
| 30 min | Decentralized AI Architectures Federated learning variants; blockchain-based smart contract coordination. |
| 10 min | Break |
| 20 min | Semantic–Neural Personalization Rule-guided KG adaptation, behavioral alignment, and filter-bubble mitigation. |
| 20 min | Knowledge-Graph-Grounded RAG Pipelines Parallel and multi-stage retrieval; building compact personalized contexts. |
| 60 min | Hands-On Exercise Participants use provided Jupyter notebooks to: • Build a small PKG using RDFLib • Run a toy federated personalization flow using Flower • Execute KG-based retrieval for LLM prompting |
| 30 min | Discussion and Q&A |
Total Duration: 3 hours 20 minutes
NoteNote
The schedule includes interactive hands-on exercises. Participants are encouraged to bring a laptop with the required software pre-installed (see Materials Needed section below).
Prerequisites
- Basic understanding of knowledge graphs
- Familiarity with recommendation systems (helpful but not required)
- Programming experience with Python (for hands-on session)