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.

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.

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Tentang alat

Melakukan larger radius mean article adalah bad atau off-topic?

Bagaimana adalah Semantik Situs Peta calculated?

Mengapa adalah beberapa articles dikecualikan?

Fitur

  • Batasan Ini rilis analyzes PatrickStox.com hanya; ini tidak rayapi atau accept unggahan. Hasil depend pada model, corpus, teks pembersihan, tag, dan klaster count. Embedding similarity dapat miss factual, navigational, commercial, dan business distinctions, dan ini tidak dapat tell apakah dua halaman seharusnya tautan.
  • Dapat I jalankan Semantik Situs Peta pada my sendiri situs web di sini?
  • Arti hasil Situs radius adalah cosine distance dari centroid dari setiap disertakan article embedding, scaled untuk readability. Centrality rank orders disertakan articles dari terkecil situs radius untuk largest. Topic radius adalah article's distance dari assigned-nya topic centroid. Topic mean/max summarizes bagaimana tightly topic's member embeddings kelompokkan together. Closest articles adalah tiga highest cosine-similarity neighbors di disertakan corpus.
  • Bagaimana untuk gunakan ini Mulai dengan distribution untuk melihat situs's overall semantik spread. Bandingkan topic mean dan maximum radii untuk temukan tight dan luas editorial neighborhoods. Filter bukti tabel oleh topic, lalu periksa paling central dan furthest halaman. Buka article untuk melihat nearest-nya semantik neighbors dan article-tingkat konteks. Bandingkan semantik structure dengan Internal Tautan Klaster Visualizer; semantik similarity dan sebenarnya internal tautan jawaban berbeda pertanyaan.
  • Tidak di ini rilis. Ini publik explorer exposes bangun-waktu analysis untuk PatrickStox.com. Ini adalah transparan kasus study, tidak general-tujuan perayap atau unggah analyzer.

Cara kerja

Adalah Semantik Situs Peta Google peringkat sinyal? Tidak. Ini berarti article adalah farther dari situs-wide semantik centroid. halaman dapat menjadi far dari global center sementara fitting tightly inside coherent topic klaster. Semantik Situs Peta Home › Alat › Semantik Situs Peta

Batasan

  • Fitur Bangun-waktu analysis dari setiap eligible diterbitkan article. Situs-wide distribution, topic coherence cards, dan lengkap bukti tabel. Pencarian, topic filtering, sorting, dan CSV ekspor. Langsung rujukan untuk article bukti dan tautan-grafik visualizer.
  • Gratis, tanpa pendaftaran. Explore bagaimana diterbitkan articles adalah distributed sekitar situs's semantik center. Temukan central halaman, coherent topic neighborhoods, dan editorial outliers di ini statis, bangun-waktu laporan tanpa treating distance sebagai kualitas score.
  • Diterbitkan, human-ditinjau article teks adalah embedded dengan semua-MiniLM-L6-v2. Cosine distance dari ternormalisasi situs centroid becomes situs radius. Deterministik spherical k-berarti supplies topic centroids dan dalam-topic distance.
  • Explore bagaimana tutup setiap diterbitkan Patrick Stox article sits untuk situs’s semantik center, topic clusters, dan nearest editorial neighbors.

Pertanyaan umum

Diterbitkan, human-ditinjau article teks adalah embedded dengan semua-MiniLM-L6-v2. Cosine distance dari ternormalisasi situs centroid becomes situs radius. Deterministik spherical k-berarti supplies topic centroids dan dalam-topic distance.

Explore bagaimana tutup setiap diterbitkan Patrick Stox article sits untuk situs’s semantik center, topic clusters, dan nearest editorial neighbors.

Adalah Semantik Situs Peta Google peringkat sinyal?

Tidak. Ini berarti article adalah farther dari situs-wide semantik centroid. halaman dapat menjadi far dari global center sementara fitting tightly inside coherent topic klaster.

Semantik Situs Peta

Home › Alat › Semantik Situs Peta

Tidak. Ini adalah situs-planning diagnostik dibangun dari satu embedding model. Google tidak provide atau endorse ini metrik.

Preview, draft, contoh, dan AI-berlabel konten adalah dikecualikan. laporan covers hanya diterbitkan editorial articles yang count toward situs-wide aggregates.