📅 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.