https://github.com/01110011011101010110010001101111/wikigraph
TigerGraph Wikipedia Sample Graph
https://github.com/01110011011101010110010001101111/wikigraph
knowledge-graph nlp tigergraph wikipedia
Last synced: about 2 months ago
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TigerGraph Wikipedia Sample Graph
- Host: GitHub
- URL: https://github.com/01110011011101010110010001101111/wikigraph
- Owner: 01110011011101010110010001101111
- Created: 2022-06-11T22:44:59.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2022-06-14T12:53:18.000Z (almost 3 years ago)
- Last Synced: 2025-01-31T11:50:11.298Z (4 months ago)
- Topics: knowledge-graph, nlp, tigergraph, wikipedia
- Language: Jupyter Notebook
- Homepage:
- Size: 42 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# WikiGraph
TigerGraph Wikipedia Sample Graph
Check out a step-by-step guide to this graph [here](https://medium.com/@shreya-chaudhary/linking-wikipedia-articles-in-a-knowledge-graph-with-tigergraph-beautifulsoup-and-yake-52dd3261a86d).
## Quickstart
1. Create a blank solution on TigerGraph Cloud.
2. Edit the credentials in the first cell of the [WikiGraph.ipynb](WikiGraph.ipynb) notebook to match your graph.
3. Run the notebook.
## Data
This data was scraped from Wikipedia via BeautifulSoup (as shown in the notebook).
## Schema
The schema consists of Wikipedia articles (`Doc`) linking to each other (`LINKS_TO`) (with a weight of links_referenced_article / total_links_in_article). In addition, entities (`Entity`) (keywords) are linked to the `Doc` vertices with a weighted edge (`DOC_ENTITY`) with the score from a keyword extraction algorithm.