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Dana je ženské křestní jméno. Podle českého kalendáře má svátek 11. prosince.
The analysis highlights Známé nositelky jména, Statistické údaje and Známí nositelé jména as prominent areas in the source structure around Dana.
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Výchozí body odvozené z tematického grafu a seřazené nezávisle na pořadí ve zdrojovém článku.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
The extracted context around Dana shows recurring relationship patterns in the source. For example, Dana → Bartůňková, Batulková, Branná, Brožková, Burešová, Cejnková, Chladeková, Dana Balatková, DanaDana Spálenská, Drábová, Dvořáčková, Federálního, Filipi, Fischerová, Hlaváčová, Homolová, Horáková, Jana FischeraDana Gillespie, Jurásková, K1Dana Jaklová Another extracted example is Dana → Britannicy, Obrázky, Wikimedia Commons Slovníkové, Wikislovníkuheslo Danu. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
jméno 11 prosince jména danuše četnost ženské svátek původu jménem tohoto původ údaje čr pořadí hebrejsky daniel změna křestní českého
TTTA extracted 65 structured relationships around Dana. Examples in this analysis include Dana → Podle údajů z roku → 2016 and Dana → Pořadí podle četnosti → 59.. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Dana | Podle údajů z roku | 2016 | 1.00 | infobox |
| Dana | Pořadí podle četnosti | 59. | 1.00 | infobox |
| Dana | Původ | hebrejský | 1.00 | infobox |
| Dana | Svátek | 11. prosince | 1.00 | infobox |
| Dana | Četnost v Česku | 50 970 | 1.00 | infobox |
| Dana | related to Externí odkazy | Obrázky | 0.60 | section |
| Dana | related to Externí odkazy | Wikimedia Commons Slovníkové | 0.60 | section |
| Dana | related to Externí odkazy | Wikislovníkuheslo Danu | 0.60 | section |
| Dana | related to Externí odkazy | Britannicy | 0.60 | section |
| Dana | related to Fiktivní postavy | Dana Fosterová | 0.60 | section |
| Dana | related to Fiktivní postavy | Krok | 0.60 | section |
| Dana | related to Fiktivní postavy | Scullyová | 0.60 | section |
The concept neighborhoods around Dana bring nearby vocabulary together. In this analysis, examples include Jménem, Danuše and Jméno. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Dana, one of the stronger structural bridges in this analysis connects Dana with Známé nositelky jména. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around Dana to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Známé nositelky jména, Statistické údaje & Známí nositelé jména, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Dana · CS edition · Analysis: TopicsToTalkAbout