Content Embedding Cluster Visualizer

Name: Content Embedding Cluster Visualizer
Price: 49 USD
Author: AAIO Inc

v1.0 documentation

Embed pages/paragraphs and plot in 2D (UMAP/t-SNE) to visually identify content clusters, gaps, overlaps, and orphan topics.

URL inputFile inputText inputXLSX export

content_embedding_visualizer.py118 lines5 paramsPython 3.8+

Quick start

terminal

pip install -r requirements.txt

terminal

python content_embedding_visualizer.py --urls https://a.com https://b.com https://c.com --output clusters.html

terminal

python content_embedding_visualizer.py --file corpus.csv --text-col content --output clusters.html

Add --output report.xlsx to save results as a spreadsheet.

Parameters

Flag	Description
`--urls`	Urls. Multiple values allowed
`--file`	CSV with text column
`--text-col`	Text col
`--method`	Method. Options: tsne, umap
`--output`	Output

help

python content_embedding_visualizer.py --help

Use cases

Content quality audit

Writer evaluation

Client deliverable

Run across all your blog posts to score quality. Sort by score in the XLSX export, then prioritize rewrites for the lowest-scoring pages.

Before publishing freelance content, run this tool to check quality signals. Use specific metrics as concrete feedback for writers.

Include the analysis in your SEO audit report. Clients appreciate data-backed recommendations over subjective opinions.

Works well with

Combine with other tools for a complete workflow:

Dependencies

Requires: beautifulsoup4, numpy, pandas, requests, scikit-learn, sentence-transformers. All included in requirements.txt.

One-time payment. Lifetime access. No monthly fees.
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AAIO Inc — aaioinc.com/tools/content_embedding_visualizer/