From Seo Wiki - Search Engine Optimization and Programming Languages
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,
and thought to be used by Google for the purpose of indexing and ranking search results in the SERPs, although no evidence has been shown of it in practice.
Topic-Sensitive PageRank is based on the PageRank algorithm, and provides a scalable approach for personalizing search rankings using Link analysis.
- Taher Haveliwala's slides describing the Topic-Sensitive PageRank algorithm
- ↑ Haveliwala, Taher (2002). "Topic-Sensitive PageRank". Proceedings of the Eleventh International World Wide Web Conference (Honolulu, Hawaii). http://infolab.stanford.edu/~taherh/papers/topic-sensitive-pagerank.pdf.
- ↑ Haveliwala, Taher (2003). "Topic-Sensitive PageRank: A Context-Sensitive Ranking Algorithm for Web Search". IEEE Transactions on Knowledge and Data Engineering. http://infolab.stanford.edu/~taherh/papers/topic-sensitive-pagerank-tkde.pdf.