AI For Unique page content

repax900

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May 30, 2022
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Hi, new here. Long term active in SEO. A year ago, I started training my own deep learning models and using (chaining) API’s (like GPT3) to make my SEO life a lot easier.

Recently I tested a python library called trafilatura. One of its features is that in can extract the main content of a given url. It works very well so far. (tested on 50+ landing pages, mostly blogs. But also product pages) It filters out headings, footer text etc.

Then I tried this: Many new customers have allot of “almost” duplicate landing pages. But screamingfrog and other seo tools wont filter those out because sentences are rewritten, or changed order.

So I created a python script which:
  • Extracted the main content of 2 similar landing pages with trafilatura
  • Used a BERT sentenceTransformer for tokenizing this content (so I get 1 Vector for each landingpage)
  • Use cosine similarity to compare these 2 vectors

Even when I shuffle the content 180 degrees this script still gives a 99% content match. So I guess if I can do this, Google must be doing this (no brainer).
I need some AI projects to work on and in this case I can expand this script further to crawl and check complete websites for content similarity.

Yet, it’s allot of work so my first question: are there any 'smart' tools doing this?

Maybe you have other suggestions. If so, I’ll share all the code here for those who are interested. Even if you’re not a programmer, it’s easy to implement.





Thanks!
 
I created this notebook so you can test for yourself:

https://colab.research.google.com/drive/1AZWIbXO8dtx6maBi6KI0Ckf7Q-PkxcIF?usp=sharing
Copy notebook to gdrive.
Click: runtime -> run everything
This may take a while.

scroll down.
In the second cell, change the urls to liking. The same urls give a 1 (100%) content similarity.
Press the play button for running this cell.

The third cell you can see the extracted content.
 
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