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Jan Klíma (* 8. prosince 1943 Vysoké Mýto) je český odborník na dějiny Portugalska, dějiny portugalsky mluvících zemí, dějiny Afriky a Latinské Ameriky.
The analysis highlights Život and Overview as prominent areas in the source structure around Jan Klíma.
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 Jan Klíma shows recurring relationship patterns in the source. For example, Jan Klíma → AngoleKLÍMA, António, AV, Bibliografie, Bibliografii, Bývalý, Databázi, Dobrodružství, Evropy, Historického, Historický, Jan, JB, Kapverským SokolůmV, Monoxylon II, Náchod, Obrázky, Oliveira Salazar, Plavba, Portugalska Another extracted example is Jan Klíma → Angola, Filozofické, Historickém, Hradci Králové, Jako, Jeana Piageta, Kapverdskou, Katedře, Luandě, Luži, Mosambiku, Od, Portugalsku, PZO Polytechna, Přednášel, Slovenské, Tatenicích, UHK, Univerzitu Hradec Králové, Vysoké. 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.
isbn praha dějiny států libri historie nakladatelství lidové noviny vyd jan klíma stručná 2015 phdr vysoké portugalska hradec rozšířené roku
TTTA extracted 48 structured relationships around Jan Klíma. Examples in this analysis include Jan Klíma → Alma mater → Univerzita Karlova and Jan Klíma → Narození → 8. prosince 1943 (82 let) Vysoké Mýto Protektorát Čechy a Morava Protektorát Čechy a Morava. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Jan Klíma | Alma mater | Univerzita Karlova | 1.00 | infobox |
| Jan Klíma | Narození | 8. prosince 1943 (82 let) Vysoké Mýto Protektorát Čechy a Morava Protektorát Čechy a Morava | 1.00 | infobox |
| Jan Klíma | Povolání | historik, polyglot, překladatel, vysokoškolský učitel a diplomat | 1.00 | infobox |
| Jan Klíma | Témata | dějiny a iberoamerikanistika | 1.00 | infobox |
| Jan Klíma | related to Externí odkazy | Obrázky | 0.60 | section |
| Jan Klíma | related to Externí odkazy | Wikimedia CommonsSeznam | 0.60 | section |
| Jan Klíma | related to Externí odkazy | Bibliografii | 0.60 | section |
| Jan Klíma | related to Externí odkazy | Historický | 0.60 | section |
| Jan Klíma | related to Externí odkazy | AV | 0.60 | section |
| Jan Klíma | related to Externí odkazy | Rozsáhlý | 0.60 | section |
| Jan Klíma | related to Externí odkazy | Historického | 0.60 | section |
| Jan Klíma | related to Externí odkazy | Databázi | 0.60 | section |
The concept neighborhoods around Jan Klíma bring nearby vocabulary together. In this analysis, examples include Klíma, Commons and Zemí. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Jan Klíma, one of the stronger structural bridges in this analysis connects Jan Klíma with Život. 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 Jan Klíma to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Život & Overview, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Jan Klíma · CS edition · Analysis: TopicsToTalkAbout