I'm searching for the Big-O complexity of PageRank algorithm.
I hardly could found anything, I just found O(n+m)
( n
- number of nodes, m
- number of arcs/edges) but I didn't believe this complexity by now.
I think it is missing the convergence criteria. I didn't think that this is a constant, I think the convergence depends on the graph diameter. It might be enough to have the Big-O for one iteration, then convergence is not important.
Nevertheless PageRank need to touch every node and aggregate every incoming rank, so I expected a runtime of O(n * m)
.
Did I miss something? Did anyone know a valuable source for the Big-O complexity of PageRank?
Thanks in advance.
This algorithm has a time complexity of O(E⋅k) where E is the number of edges and k is the number of iterations. The number of iterations is data-dependent, but the user can set a maximum.
The PageRank ScoreA PageRank score of 0 is typically a low-quality website, whereas, on the other hand, a score of 10 would represent only the most authoritative sites on the web.
Does Google still use PageRank? Yes, Google does still uses PageRank. While it may not be a metric that website owners have access to, it is still used in their algorithms. A tweet by John Mueller, a Senior Webmaster Trends Analyst at Google, solidifies that PageRank is still used as a ranking signal.
PageRank was named after Larry Page, one of the founders of Google. PageRank is a way of measuring the importance of website pages. According to Google: PageRank works by counting the number and quality of links to a page to determine a rough estimate of how important the website is.
After some research and further thinking I have come to the conclusion that O(n+m)
ist the real thing.
Because even in a complete graph, one has to touch each edge twice. One could not touch every edge, that was the mistake in my thinkings. Therefor one has to touch at least every node, which is n times and two times each edge which is m in big O.
So the correct answer is O(n+m)
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