📅 2024-09-16 — Session: Automated Government Resolution Analysis Project
🕒 16:30–16:40
🏷️ Labels: Automation, Government, NLP, Knowledge Graph, Project Management
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The primary goal of this session was to develop a project for automating the extraction and analysis of government resolutions. The focus was on a specific subsecretary, with the aim of generating a knowledge graph to enhance task assignment and operational efficiency.
Key Activities
- Project Simulation Breakdown: Detailed a project simulation for automating the extraction of government resolutions, including team roles, responsibilities, and a structured roadmap for task assignments.
- NLP and Data Scraping: Simulated a project focused on scraping government resolutions using NLP for data extraction, organizing collaborative roles for the project’s initial preparation phase.
- Daily Task Outlining: Outlined specific tasks for the Project Manager and Lead Developer, focusing on project goals, team roles, technical setup, and initial development steps.
- PDF Text Extraction Automation: Developed a step-by-step process for extracting text from PDF links using Python, integrating libraries like PyPDF2 or pdfplumber.
Achievements
- Created a comprehensive project plan for automating government resolution analysis, including a detailed simulation of team roles and responsibilities.
- Established a framework for using NLP in data extraction and knowledge graph construction.
- Defined daily tasks for key project roles to ensure smooth execution.
- Automated PDF text extraction process, enhancing data processing capabilities.
Pending Tasks
- Further refinement of the NLP models for more accurate data extraction.
- Testing and validation of the automated PDF text extraction process to ensure reliability.