https://github.com/naphattha/a-financial-knowledge-graph-construction-from-set50-annual-reports

This project builds a Financial Knowledge Graph from SET50 data, comparing its query efficiency and accuracy with a relational database to enhance complex financial analysis.
https://github.com/naphattha/a-financial-knowledge-graph-construction-from-set50-annual-reports

chatbot-integration financial-data-analysis financial-knowledge-graph mysql neo4j python

Last synced: 4 days ago
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This project builds a Financial Knowledge Graph from SET50 data, comparing its query efficiency and accuracy with a relational database to enhance complex financial analysis.

• Host: GitHub
• URL: https://github.com/naphattha/a-financial-knowledge-graph-construction-from-set50-annual-reports
• Owner: naphattha
• Created: 2024-10-31T17:18:18.000Z (about 2 months ago)
• Default Branch: main
• Last Pushed: 2024-11-01T03:23:35.000Z (about 2 months ago)
• Last Synced: 2024-12-19T22:29:30.059Z (4 days ago)
• Topics: chatbot-integration, financial-data-analysis, financial-knowledge-graph, mysql, neo4j, python
• Language: Jupyter Notebook
• Homepage:
• Size: 844 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# A Financial Knowledge Graph Construction from SET50 Annual Reports

This project provides a chatbot interface to query financial data for SET50 companies. It compares performance between two databases, Neo4j (graph-based) and MySQL (relational), in handling complex financial queries. The project leverages a Large Language Model (LLM) for natural language interpretation.

Project Structure

 * llm-chatbot-python-neo4j: Contains code for Neo4j database integration.

 * llm-chatbot-python-mysql: Contains code for MySQL database integration.

Each directory includes the necessary files to run an independent instance of the chatbot application.