Table of Contents
The Challenge #
Texts overloaded with keywords (Keyword Stuffing) are easily detected and penalized by NLP algorithms. It’s crucial not only to include keywords but to connect them naturally.
The Solution #
- Proximity Analysis: The platform measures the semantic distance between related phrases. The application calculates the distance between keywords directly through the site’s structure (DOM tree).
- Virtual Penalties: If keywords are separated by a period, a paragraph break, or an HTML block transition, the algorithm increases the semantic distance. The system accounts for transitions between blocks and applies multiple types of penalties (hard and soft breaks: from punctuation and brackets to external links).
- Hard Breaks: If an external link stands between them, the connection is severed (Hard Break).
- Semantic Issues (Diagnostics): The platform automatically scans the text in a natural reading order (left-to-right) and highlights anomalies where logic sags, semantic connections are broken, and keywords are placed too far apart.
You receive a clear Action Plan to improve content readability and cohesion.
