Topic-Sensitive PageRank
From Infogalactic: the planetary knowledge core
Topic-Sensitive PageRank (commonly referred to as TSPR) is a context-sensitive ranking algorithm for web search developed by Taher Haveliwala while at Stanford University, [1] [2] and thought to be used by Google for the purpose of indexing and ranking search results in the search engine results pages, although no evidence has been shown of it in practice.[citation needed]
Algorithm
Topic-Sensitive PageRank is based on the PageRank algorithm, and provides a scalable approach for personalizing search rankings using Link analysis.
Related Resources
- Taher Haveliwala's slides describing the Topic-Sensitive PageRank algorithm
See also
References
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Further reading
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