Automated Text Summarizer
An extractive summarization tool using TF-IDF and sentence scoring.
Overview
This tool condenses long articles into a few key sentences. It works by calculating the TF-IDF (Term Frequency-Inverse Document Frequency) score for words, scoring sentences based on the weight of the words they contain, and selecting the top-scoring sentences to form the summary.
Challenges & Solutions
Ensuring the summary is coherent and grammatically correct was a challenge for this extractive method. While not perfect, the model's output was improved by ranking sentences not just by score but also by their original position in the text.
Key Features
- Real-time processing and analysis
- Scalable architecture design
- User-friendly interface
- Comprehensive documentation