Data extraction and RAG: leveraging LLM for time series prediction
Borrelli, Fabrizio (A.A. 2024/2025) Data extraction and RAG: leveraging LLM for time series prediction. Tesi di Laurea in Data-driven models for investment, Luiss Guido Carli, relatore Antonio Simeone, pp. 48. [Master's Degree Thesis]
Full text for this thesis not available from the repository.
Abstract/Index
Literature review. Stock market forecasting. Natural language processing in financial contexts. Retrieval-augmented generation (RAG). Graph-based retrieval-augmented generation (GraphRAG). Methodological framework. Data sources and acquisition. NLP-based data enrichment processes. Knowledge graph construction and schema. Knowledge graph support for the multi-agent GraphRAG system. Multi-agent GraphRAG system. System architecture overview. Specialized agents and their roles. Multi-phase reasoning process. Traditional RAG vs. GraphRAG vs. multi-agent GraphRAG. Traditional RAG (document-based retrieval-augmented generation). GraphRAG (knowledge-graph-augmented generation). Multi-agent GraphRAG.
References
Bibliografia: p. 48.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Data Science e Management (LM-91) |
| Chair: | Data-driven models for investment |
| Thesis Supervisor: | Simeone, Antonio |
| Thesis Co-Supervisor: | Martino, Alessio |
| Academic Year: | 2024/2025 |
| Session: | Summer |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 30 Sep 2025 10:09 |
| Last Modified: | 30 Sep 2025 10:09 |
| URI: | https://tesi.luiss.it/id/eprint/43375 |
Downloads
Downloads per month over past year
Repository Staff Only
 |
View Item |
