MATHEMATICS BEHIND GOOGLE PAGERANK ALGORITHM

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MATHEMATICS BEHIND GOOGLE PAGERANK ALGORITHM ( mathematics-behind-google-pagerank-algorithm )

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Google. (n.d.). How we started and where we are today. Retrieved February 06, 2018, from https://www.google.com/about/our-story/ Google. (n.d.). Facts about Google and Competition. Retrieved February 06, 2018, from https://web.archive.org/web/20130702063520/https://www. google.com/competition/howgooglesearchworks.html Haveliwala, T., & Kamvar, S. (2003). The Second Eigenvalue of the Google Matrix. Stanford University Technical Report. Retrieved from: http://ilpubs.stanford.edu:8090/582 Hirsch, J. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102 (46), 16569-16572; DOI: 10.1073/pnas.0507655102 Iván, G., & Grolmusz, V. (2011). When the Web meets the cell: using personal- ized PageRank for analyzing protein interaction networks. Bioinformatics, 27(3), 405-407. DOI: 10.1093/bioinformatics/btq680 Meyer, C. (Ed.) (2000). Matrix Analysis and Applied Linear Algebra. Philadel- phia, PA: Soc. for Industrial and Applied Math. Sangers, A. & van Gijzen, M. (2015). The eigenvectors corresponding to the second eigenvalue of the Google matrix and their relation to link spamming. Journal of Computational and Applied Mathematics 277, 192-201 Wall, A. (2017). History of Search Engines: From 1945 to Google Today. Re- trieved from http://www.searchenginehistory.com/ Wills, R. S. (2007). When Rank Trumps Precision: Using the Power Method to Compute Google’s PageRank (Doctoral Dissertation). Retrieved from https://repository.lib.ncsu.edu/handle/1840.16/4953 Yan, E., & Ding, Y. (2010). Discovering author impact: A PageRank perspective. Information Processing and Management, 47, 125-134. DOI: 10.1016/j.ipm.2010.05.002. 36

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