📅 2025-01-11 — Session: Development of Summarization and Content Frameworks
🕒 15:40–20:30
🏷️ Labels: Summarization, Content Adaptation, AI, Python, Economic Research
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The goal of this session was to develop and refine frameworks for summarization and content adaptation, as well as to enhance data processing methods and AI prompt engineering.
Key Activities
- Developed a model for a ‘Nota de Falecimento’ template, providing a standard format for funeral announcements.
- Outlined a content adaptation framework for transforming thesis chunks into various content types, including blog posts and tutorials.
- Explored covariance matrix decomposition and notation analysis, focusing on statistical implications.
- Created guidelines for summarizing complex texts and structured summarization frameworks for thesis sections.
- Proposed a summarization and triaging system for academic content evaluation.
- Implemented a
ThesisAnalyzerclass for processing thesis chunks and generating structured summaries. - Updated methods for better error handling and data processing using Python and OpenAI API.
- Conducted a comparative analysis of thesis summaries and proposed enhancements to summarization prompts.
- Planned textbook development and high-impact research paper ideas in economics.
Achievements
- Established comprehensive frameworks for content adaptation and summarization.
- Improved AI prompt engineering and data processing techniques.
- Developed actionable insights for economic research and academic writing.
Pending Tasks
- Further refinement of AI-generated summaries and prompt enhancements.
- Implementation of proposed textbook and research paper ideas.
Outcome
The session successfully laid the groundwork for improved content strategies and data processing capabilities, enhancing both academic and practical applications.