40 lines
1.8 KiB
Markdown
40 lines
1.8 KiB
Markdown
# Domain Ranking
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Contains domain ranking algorithms. The domain ranking algorithms are based on
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the JGraphT library.
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Two principal algorithms are available, the standard PageRank algorithm,
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and personalized pagerank; each are available for two graphs, the link graph
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and a similarity graph where each edge corresponds to the similarity between
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the sets of incident links to two domains, their cosine similarity acting as
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the weight of the links.
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With the standard PageRank algorithm, the similarity graph does not produce
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anything useful, but something magical happens when you apply Personalized PageRank
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to this graph. It turns into a very good "vibe"-sensitive ranking algorithm.
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It's unclear if this is a well known result, but it's a very interesting one
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for creating a ranking algorithm that is focused on a particular segment of the web.
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## Central Classes
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* [PageRankDomainRanker](src/main/java/nu/marginalia/ranking/PageRankDomainRanker.java) - Ranks domains using the
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PageRank or Personalized PageRank algorithm depending on whether a list of influence domains is provided.
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### Data sources
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* [LinkGraphSource](src/main/java/nu/marginalia/ranking/data/LinkGraphSource.java) - fetches the link graph
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* [InvertedLinkGraphSource](src/main/java/nu/marginalia/ranking/data/InvertedLinkGraphSource.java) - fetches the inverted link graph
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* [SimilarityGraphSource](src/main/java/nu/marginalia/ranking/data/SimilarityGraphSource.java) - fetches the similarity graph from the database
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Note that the similarity graph needs to be precomputed and stored in the database for
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the similarity graph source to be available.
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## See Also
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* [result-ranking](../result-ranking) - Ranks search results
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## Useful Resources
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* [The PageRank Citation Ranking: Bringing Order to the Web](http://ilpubs.stanford.edu:8090/422/1/1999-66.pdf)
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