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1)~the local PageRanks of pages for each host are computed independently using the link structure of that host, (2)~these local PageRanks are then weighted by the ``importance'' of the corresponding host, and (3)~the standard PageRank algorithm is then run using as its starting vector the weighted aggregate of the local PageRanks.
This paper is based on work supported in part by the National Science Foundation under Grant No.\ IIS-0085896.
This is the same grant that supports Topic-Sensitive PageRank [dbpubs.stanford.edu]
The NSF grant award is located here:
https:*//www.fastlane.nsf.gov/servlet/showaward?award=0085896
More on the Global InfoBase Project [webmasterworld.com]
There is a huge interest in improving PageRank and it is shown here by both the sponsors and the researchers.
Remember, these PageRank papers that come out of Stanford are basically proposals for improving the original algorithm. This in no way means that Google is using some of what is proposed now or that they will use them in the future. However, Google and Stanford work together on many research tasks. A few researchers actually go on temporary leave from Stanford to consult with Google.
The fact that continual research is being done into better and better, more refined algorithms for IR is a good thing for everybody.
PageRank has certainly made the web a much more useful beast for many millions of people. By advancing it, I am certain that millions more will be able to enjoy even greater utility from the internet.
did you catch this related one?
I/O efficient techniques for computing pagerank:
[cis.poly.edu...]
