Similarity Checker Between Two Texts

Content Similarity between two pages can lead to duplicate content issues which is a massive problem in SEO. This problem can lead to Technical SEO Issues like.

  1. Duplicate Google Chose Different Canonical than User
  2. Alternative Page with Proper Canonical Tag
  3. Page not getting indexed

Just imagine, you have a website that has implemented Programmatic SEO strategy for location based pages but certain location pages aren’t indexed because of the availability of duplicate content share between both the pages.

To resolve & identify issues like these I have built this tool where you can paste text content from two pages & understand the duplicate content share between both the pages.

What’s the algorithm this tool uses to determine content similarity between two text?

This tool is based on a backend Python Script that makes use of TF-IDF (Term Frequency Inverse Document Frequency) Vectorization in conjunction with Cosine Similarity. 

Based on the pasted text, the same text is converted into vectors. Vectors is a numerical representation of the text wherein words are assigned a numerical value based on the importance they carry in the phrase or sentence now cosine similarity is calculated between the vectors. This makes the similarity check calculation very reliable.

You can use cosine similarity to compare your two pSEO pages with your competitor’s two pSEO pages. This will help you see if your pages have more duplication, are on par, or are better than your competitors.

Leave a Comment