📅 2025-02-17 — Session: Enhanced NLP Text Processing and Document Automation
🕒 16:05–16:30
🏷️ Labels: NLP, RAKE, Python, Word Automation, Keyword Extraction
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to enhance the efficiency and effectiveness of NLP text processing pipelines and automate document creation tasks.
Key Activities
- Streamlined an NLP text processing script focusing on efficiency and readability, including structured sections for loading, preprocessing, extracting topics and keywords, and saving results.
- Conducted a critical analysis of the RAKE keyword extraction method, identifying verbosity issues and proposing improvements.
- Adjusted RAKE parameters to improve the balance between keyword quantity and relevance.
- Automated the creation of a Word document based on a provided image, ensuring the requested formatting was applied.
- Provided detailed instructions on changing page orientation in Microsoft Word, covering both entire documents and specific pages.
Achievements
- Improved the NLP text processing pipeline for better performance and clarity.
- Enhanced RAKE keyword extraction method with more relevant keyword outputs.
- Successfully automated the generation of a formatted Word document.
Pending Tasks
- Further testing and validation of the adjusted RAKE parameters in diverse datasets.
- Exploration of additional NLP techniques for topic modeling and keyword extraction.