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Hugo je mužské křestní jméno germánského původu. Vzniklo jako zkrácenina ke staroněmeckým jménům začínajícím na Hug- (např. Hugubert, Hugubald, Huguwin…). Vykládá se jako „duch“, „mysl“. Pochází z pragermánského *hugaz; stejný původ s anglosaským hugi, starohorskoněmeckým hugu, hugi, staronorským hugr.
The analysis highlights Hugo v jiných jazycích, Známí nositelé jména and Hugo jako postava v animovaných filmech as prominent areas in the source structure around Hugo.
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 Hugo shows recurring relationship patterns in the source. For example, Hugo → Andrian-Belcredi, Anny KyjevskéHugo Weaving, Ball, Bergmann, Berks, Bernarda, Bezděk, Boettinger, Bonneville, Boss, Champagne, ClairvauxHugo Chávez, Cluny, ClunyHugo Baar, Dancy, Demartini, Distler, Falcandus, Feigl, František Königsegg-Rottenfels Another extracted example is Hugo → Hugasrusky, Hughlatinsky, Hugolínpolsky, Hugonanglicky, Hugonis, Hugoslovensky, Hugue, Huguesitalsky, Hugófrancouzsky, Huw, Ugolitevsky. 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.
svátek jméno jako jména původ dubna politik původu jsou četnost hugi mužské hugh německý spisovatel český herec francouzský ke např
TTTA extracted 94 structured relationships around Hugo. Examples in this analysis include Hugo → Podle údajů z roku → 2009 and Hugo → Pořadí podle četnosti → 230.. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Hugo | Podle údajů z roku | 2009 | 1.00 | infobox |
| Hugo | Pořadí podle četnosti | 230. | 1.00 | infobox |
| Hugo | Původ | germánský | 1.00 | infobox |
| Hugo | Svátek | 1. dubna | 1.00 | infobox |
| Hugo | Četnost v Česku | 649 | 1.00 | infobox |
| Hugo | related to Externí odkazy | Obrázky | 0.60 | section |
| Hugo | related to Externí odkazy | Wikimedia Commons Slovníkové | 0.60 | section |
| Hugo | related to Externí odkazy | Wikislovníku | 0.60 | section |
| Hugo | related to Hugo jako postava v animovaných filmech | Bobo | 0.60 | section |
| Hugo | related to Hugo jako postava v animovaných filmech | Macourek | 0.60 | section |
| Hugo | related to Hugo jako postava v animovaných filmech | Doubrava | 0.60 | section |
| Hugo | related to Hugo jako postava v animovaných filmech | BornHugo | 0.60 | section |
The concept neighborhoods around Hugo bring nearby vocabulary together. In this analysis, examples include Jméno, Jména and Hugh. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Hugo, one of the stronger structural bridges in this analysis connects Hugo with Známí nositelé 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 Hugo to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Hugo v jiných jazycích, Známí nositelé jména & Hugo jako postava v animovaných filmech, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Hugo · CS edition · Analysis: TopicsToTalkAbout