Sprachen

Semantic Site Map

Free, no signup. Explore how 0 published articles are distributed around this site's semantic center. Find central pages, coherent topic neighborhoods, and editorial outliers in this static, build-time report without treating distance as a quality score.

Built by Patrick Stox

Current build-time report · eligible published corpus

Report generated Aug 23, 2026.

This is a precomputed public report — filters and sorting run in your browser, and nothing you enter is sent or stored. Anonymous run-level outcome counters may be used for aggregate research; URLs, domains, IPs, and identifiers are never included, and no statistic is released below 100 runs.

Semantic Site Map has no eligible published articles to analyze in this build. Preview, draft, example, and AI-labeled entries are intentionally excluded.

0included articles
0most central radius
0furthest radius
0semantic topics

Site-radius distribution

Each dot is an article. Select one to open its article-level AI + SEO Data view.

Use the table ↓
more central · 0further out · 0

The horizontal position is relative to this report's observed minimum and maximum; it is not a universal 0–100 grade.

Topic coherence

Lower mean distance means the articles in that model-created cluster sit closer together.

Topic coherence needs enough eligible articles to form more than one meaningful cluster. No topic comparison is available in this build.

Article evidence

Search, filter, and sort the complete included set.

Showing 0 articles

ArticleSite radiusTopicTopic radiusClosest articles

How to use it

  1. Start with the distribution to see the site's overall semantic spread.
  2. Compare topic mean and maximum radii to find tight and broad editorial neighborhoods.
  3. Filter the evidence table by topic, then inspect the most central and furthest pages.
  4. Open an article to see its nearest semantic neighbors and article-level context.
  5. Compare semantic structure with the Internal Link Cluster Visualizer; semantic similarity and actual internal links answer different questions.

What the results mean

  • Site radius is cosine distance from the centroid of every included article embedding, scaled for readability.
  • Centrality rank orders the included articles from the smallest site radius to the largest.
  • Topic radius is an article's distance from its assigned topic centroid.
  • Topic mean/max summarizes how tightly the topic's member embeddings group together.
  • Closest articles are the three highest cosine-similarity neighbors in the included corpus.

Features

  • Build-time analysis of every eligible published article.
  • Site-wide distribution, topic coherence cards, and complete evidence table.
  • Search, topic filtering, sorting, and CSV export.
  • Direct handoff to article evidence and the link-graph visualizer.

Limitations

This release analyzes PatrickStox.com only; it does not crawl or accept uploads. Results depend on the model, corpus, text cleanup, tags, and cluster count. Embedding similarity can miss factual, navigational, commercial, and business distinctions, and it cannot tell whether two pages should link.

Frequently asked questions

Can I run Semantic Site Map on my own website here?

Not in this release. This public explorer exposes the build-time analysis for PatrickStox.com. It is a transparent case study, not a general-purpose crawler or upload analyzer.

Does a larger radius mean an article is bad or off-topic?

No. It means the article is farther from the site-wide semantic centroid. A page can be far from the global center while fitting tightly inside a coherent topic cluster.

How is Semantic Site Map calculated?

Published, human-reviewed article text is embedded with all-MiniLM-L6-v2. Cosine distance from the normalized site centroid becomes the site radius. Deterministic spherical k-means supplies topic centroids and within-topic distance.

Why are some articles excluded?

Preview, draft, example, and AI-labeled content is excluded. The report covers only published editorial articles that count toward site-wide aggregates.

Is Semantic Site Map a Google ranking signal?

No. It is a site-planning diagnostic built from one embedding model. Google does not provide or endorse this metric.

Local data

Saved targets, named lists, and recent check summaries remain only in this browser.

Feedback
Report a bug

Found something broken in Siteradius? Let us know what happened — this goes straight to a private triage queue, not a public list.

What will be sent 
 No tool inputs, uploads, pasted source, complete results, query parameters, or URL fragments are attached automatically. You can edit or remove the selected passage above. Browser and anti-abuse metadata is processed for spam prevention. 
  
 
  
 
 
  
 
 
   
People also explore
ToolVideo SEO CheckerToolPDP SEO CheckerToolNews SEO CheckerArticleSite ArchitectureArticleHow to Build a Silo Structure: A Practical GuideArticleRetrieval-Augmented Generation (RAG)
 
 
 
Feature requests for Siteradius
 

Upvote what you want most. New ideas can be submitted from the floating Feedback menu;
      requests appear here once approved, and the most-wanted rise to the top.

   
Loading…
  
  ➕ Request a feature   
New requests are reviewed before they appear here.
 
     
  
  
 
 
 
 
     
     
Über das Tool
Erkunde, wie veröffentlichte Patrick-Stox-Artikel um das semantische Zentrum dieser Website verteilt sind. Der Build-Time-Bericht zeigt Site-Radius, Themenkohärenz, zentrale und entfernte Seiten sowie die nächsten redaktionellen Nachbarn; ein Abstand ist kein Qualitäts- oder Google-Ranking-Score.
Nur veröffentlichte, human-reviewed redaktionelle Artikel zählen. Vorschau-, Draft-, Beispiel- und AI-gelabelte Inhalte bleiben ausgeschlossen.
Funktionen
  • Build-Time-Analyse jedes geeigneten veröffentlichten Artikels
  • Site-weite Verteilung, Themenkarten und vollständige Evidenztabelle
  • Suche, Themenfilter, Sortierung und CSV-Export
  • Direkte Übergabe an Artikel-Evidenz und den Internal-Link-Cluster-Visualizer
Funktionsweise
Beginne mit der Verteilung für die semantische Streuung der Website. Vergleiche Topic-Mittel- und Maximalradien, filtere die Evidenztabelle nach Thema und öffne zentrale oder weit entfernte Seiten. Öffne einen Artikel für seine nächsten semantischen Nachbarn und vergleiche die Struktur mit dem Internal-Link-Cluster-Visualizer; semantische Ähnlichkeit und tatsächliche Links beantworten unterschiedliche Fragen.
Einschränkungen
  • Diese Veröffentlichung analysiert nur PatrickStox.com und akzeptiert weder Uploads noch eigene Websites.
  • Ergebnisse hängen von Modell, Korpus, Textbereinigung, Tags und Clusteranzahl ab; Embedding-Ähnlichkeit verfehlt möglicherweise faktische, navigative, kommerzielle und geschäftliche Unterschiede.
  • Der Bericht kann nicht bestimmen, ob zwei Seiten verlinken sollten, und Google stellt diesen Messwert weder bereit noch empfiehlt es ihn.
Häufig gestellte Fragen
Wie wird die Semantische Sitemap berechnet?
Veröffentlichter, human-reviewed Artikeltext wird mit all-MiniLM-L6-v2 eingebettet. Die Cosinusdistanz zum normalisierten Site-Zentroid wird zum Site-Radius; deterministisches sphärisches k-means liefert Topic-Zentroiden und Distanzen innerhalb des Themas.
Bedeutet ein größerer Radius, dass ein Artikel schlecht oder off-topic ist?
Nein. Er ist weiter vom globalen Site-Zentrum entfernt, kann aber eng in ein kohärentes Themencluster passen.
Warum sind manche Artikel ausgeschlossen?
Preview-, Draft-, Beispiel- und AI-gelabelte Inhalte werden ausgeschlossen. Der Bericht deckt nur veröffentlichte redaktionelle Artikel ab, die in Site-Aggregate zählen.
Kann ich die Semantische Sitemap für meine eigene Website ausführen?
Nicht in dieser Veröffentlichung. Der öffentliche Explorer zeigt die Build-Time-Analyse von PatrickStox.com als transparentes Fallbeispiel, nicht als allgemeinen Crawler oder Upload-Analyzer.