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BERT Semantic Interlinker

Uses Sentence Transformers and embeddings to find semantic relationships between pages for intelligent internal linking. Award-winning Streamlit App of the Month.

Features

  • Sentence Transformer embeddings
  • Semantic similarity scoring
  • Bulk page analysis
  • Export to CSV

What you'll need

  • Screaming Frog crawl export (internal_html.csv)
  • Or any CSV with URL and content columns

How to use

  1. 1 Export your crawl data from Screaming Frog or prepare a CSV with URLs
  2. 2 Upload the file to the Streamlit app
  3. 3 Select which columns contain your URLs and content
  4. 4 Set similarity threshold and run the analysis
  5. 5 Download the results with linking recommendations

What you get

CSV file containing semantically related page pairs with similarity scores, ready for implementation.

When to use this

  • Building topic clusters with contextual internal links
  • Finding orphan pages that need more internal links
  • Improving site architecture based on content relationships
  • Scaling internal linking for large eCommerce sites
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Want me to run this for you?

I offer this as a managed service. You get the insights without touching the tool.

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