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David Arthur Eppstein (born 1963) is an American computer scientist and mathematician. He is a distinguished professor of computer science at the University of California, Irvine, known for his work in computational geometry, graph algorithms, and recreational mathematics. Eppstein is also a Wikipedia editor and an administrator on the English Wikipedia.
The analysis highlights Research, Career, Art and Science as prominent areas in the source structure around David Eppstein.
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 Eppstein shows recurring relationship patterns in the source. For example, David Eppstein → California, DBLP Bibliography Server David, Eppstein, Google Scholar, IrvineDavid Eppstein, University, User, WikipediaDavid Eppstein's Another extracted example is David Eppstein → Columbia University, Stanford University. 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.
eppstein doi isbn david computer science university graph algorithms 10 symposium wikipedia irvine geometry mathematics pdf also editor california computational
TTTA extracted 24 structured relationships around David Eppstein. Examples in this analysis include David Eppstein → Alma mater → Stanford University and David Eppstein → Alma mater → Columbia University. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| David Eppstein | Alma mater | Stanford University | 1.00 | infobox |
| David Eppstein | Alma mater | Columbia University | 1.00 | infobox |
| David Eppstein | Born | David Arthur Eppstein 1963 (age 62–63) Windsor, England | 1.00 | infobox |
| David Eppstein | Citizenship | United States | 1.00 | infobox |
| David Eppstein | Doctoral advisor | Zvi Galil | 1.00 | infobox |
| David Eppstein | Fields | Computational geometry | 1.00 | infobox |
| David Eppstein | Fields | Graph algorithms | 1.00 | infobox |
| David Eppstein | Thesis | Efficient algorithms for sequence analysis with concave and convex gap costs (1989) | 1.00 | infobox |
| David Eppstein | Website | 11011110.github.io/blog | 1.00 | infobox |
| David Eppstein | Workplaces | University of California, Irvine | 1.00 | infobox |
| finite element meshing | instance of | He has published also in application areas | 0.80 | text |
| which is used in engineering design | instance of | He has published also in application areas | 0.80 | text |
The concept neighborhoods around David Eppstein bring nearby vocabulary together. In this analysis, examples include Eppstein, Pdf and Paths. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For David Eppstein, one of the stronger structural bridges in this analysis connects David Eppstein with Education and career. 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 Eppstein to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Research, Career, Art & Science, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — David Eppstein · EN edition · Analysis: TopicsToTalkAbout