Mathematical properties and analysis of Google's PageRank

By Ilse C. F. Ipsen, Rebecca S. Wills. 2008

50 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Deepesh Data
2. Linqi Song
3. Suhas N. Diggavi
4. Bu-Sung Lee
5. Jianshu Weng
6. Chenliang Li
7. Sai Praneeth Karimireddy
8. Damiano Spina

Citations in the corpus

• Data Encoding for Byzantine-Resilient Distributed Optimization (2019, methodology): “…of them include (i) the power method for computing the largest eigenvalue of a diagonalizable matrix, which is used in Google’s PageRank algorithm [ISW06], Twitter’s recommendation system [GGL + 13], etc.; (ii) iterative methods for solving sparse linear systems [Saa03]; (iii) many graph…”
• Event Detection in Twitter (2011, background): “This can be efficiently solved by power iteration, which is able to scale up with the increase of the number of words used in tweets (Ipsen and Wills 2006)”