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David je mužské jméno pocházející z dávno zaniklé ugaritštiny (patřící stejně jako hebrejština do semitské jazykové skupiny), v níž znamená davidu „náčelník“, lidová etymologie jej spojuje s hebrejským dód „miláček“ a „strýček“. K 22. dubnu 2002 nosilo toto jméno 68 281 obyvatel Česka, čímž bylo 21. nejčastějším mužským jménem. V českém občanském…
The analysis highlights Známí nositelé, Statistické údaje and Související články as prominent areas in the source structure around David.
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.
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 David shows recurring relationship patterns in the source. For example, David → Balda, Beckham, Belle, Ben Gurion, Berkowitz, Boreanaz, Bowie, Byron, Copperfield, Coulthard, David Attenborough, DJDave Grohl, Eben, Ferrer, Gahan, Gemmell, Gilmour, Grudl, Guetta, Hilbert Another extracted example is David → Anglicky, DavideFinsky, DavidMaďarsky, DavíðRusky, DawidItalsky, DávidPolsky, TaavettiIslandsky. 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 mužské 30 prosince příjmení král tohoto jména četnost svátek jako 2002 skotský skupiny původ údaje čr pořadí údajů ugaritštiny
TTTA extracted 73 structured relationships around David. Examples in this analysis include David → Podle údajů z roku → 2016 and David → Pořadí podle četnosti → 29.. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| David | Podle údajů z roku | 2016 | 1.00 | infobox |
| David | Pořadí podle četnosti | 29. | 1.00 | infobox |
| David | Původ | hebrejský | 1.00 | infobox |
| David | Svátek | 30. prosince | 1.00 | infobox |
| David | Četnost v Česku | 101 311 | 1.00 | infobox |
| David | related to Další | David Attenborough | 0.60 | section |
| David | related to Další | Balda | 0.60 | section |
| David | related to Další | Belle | 0.60 | section |
| David | related to Další | Beckham | 0.60 | section |
| David | related to Další | Berkowitz | 0.60 | section |
| David | related to Další | Boreanaz | 0.60 | section |
| David | related to Další | Bowie | 0.60 | section |
The concept neighborhoods around David bring nearby vocabulary together. In this analysis, examples include Král, Příjmení and Jméno. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For David, one of the stronger structural bridges in this analysis connects David with Známí nositelé. 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 David to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Známí nositelé, Statistické údaje & Související články, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — David · CS edition · Analysis: TopicsToTalkAbout