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GraphHopper is an open-source routing library and server written in Java and provides a routing API over HTTP. It runs on the server, desktop, Android, iOS or Raspberry Pi. By default OpenStreetMap data for the road network and elevation data from the Shuttle Radar Topography Mission is used. The front-end is open-source too and called GraphHopper Maps.
The analysis highlights Applications and Companies as prominent areas in the source structure around GraphHopper.
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 GraphHopper shows recurring relationship patterns in the source. For example, GraphHopper → Cluster API, Distance Matrix API, Geocoding API, GraphHopper GmbH, Isochrone API, Map Matching API, Profiles API, Route Optimization API, Routing API, The GraphHopper Directions API Another extracted example is GraphHopper → APIs, Deutsche Bahn, Flixbus, Gnome, Komoot, March, Notable, OpenStreetMap, Rome2rio, Since February. 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.
routing java openstreetmap gps navigation api open-source server default data road network used use different make fast vehicles planning written
TTTA extracted 33 structured relationships around GraphHopper. Examples in this analysis include GraphHopper → Developer → GraphHopper community and GraphHopper → License → Apache License 2.0. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| GraphHopper | Developer | GraphHopper community | 1.00 | infobox |
| GraphHopper | License | Apache License 2.0 | 1.00 | infobox |
| GraphHopper | Operating system | Cross-platform | 1.00 | infobox |
| GraphHopper | Repository | github.com/graphhopper/graphhopper | 1.00 | infobox |
| GraphHopper | Stable release | 11.0 / 14 October 2025; 10 months ago (14 October 2025) | 1.00 | infobox |
| GraphHopper | Type | Search, Graph and GPS navigation software | 1.00 | infobox |
| GraphHopper | Website | graphhopper.com | 1.00 | infobox |
| GraphHopper | Written in | Java | 1.00 | infobox |
| GraphHopper | is a | open-source routing library and server written in Java and provides a routing API over HTTP | 0.90 | text |
| Dijkstra | instance of | The front-end is open-source too and called GraphHopper Maps.GraphHopper can be configured to use different algorithms | 0.80 | text |
| A | instance of | The front-end is open-source too and called GraphHopper Maps.GraphHopper can be configured to use different algorithms | 0.80 | text |
| GraphHopper | related to Company | In January | 0.60 | section |
The concept neighborhoods around GraphHopper bring nearby vocabulary together. In this analysis, examples include Routing, Api and Apache. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For GraphHopper, one of the stronger structural bridges in this analysis connects GraphHopper with Overview. 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 GraphHopper to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Applications & Companies, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — GraphHopper · EN edition · Analysis: TopicsToTalkAbout