📅 2025-03-01 — Session: Email Data Analysis and Keyword Extraction
🕒 03:05–03:40
🏷️ Labels: Data Analysis, Email Communication, Keyword Extraction, LDA, RAKE, NLP
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to analyze email data and enhance keyword extraction techniques using Python and NLP methods.
Key Activities
- DataFrame Filtering: Implemented a Python function to filter email data based on sender and receiver addresses.
- Email Data Insights: Generated insights from email exchanges, focusing on collaboration patterns and communication themes.
- LDA Keyword Extraction: Applied LDA for keyword extraction, involving text preprocessing and topic visualization.
- LDA Output Analysis: Evaluated LDA results and suggested improvements for better topic separation.
- RAKE Optimization: Improved RAKE keyword extraction by addressing issues with irrelevant metadata and generic words.
- RAKE Evaluation: Assessed RAKE output quality and proposed enhancements using Named Entity Recognition and LDA.
Achievements
- Successfully filtered and analyzed email data, extracting meaningful insights and keywords.
- Enhanced keyword extraction processes using LDA and RAKE, improving accuracy and relevance.
Pending Tasks
- Further refine keyword extraction methods by integrating additional NLP techniques and tools.