Researchers at Stanford University have developed several new
techniques that together may make it possible to calculate Web
page rankings as used in the Google search engine up to five
times faster. The speed-ups to Google's method may make it
realistic to calculate page rankings personalized for an
individual's interests or customized to a particular topic.
Computing PageRank, the ranking algorithm behind the Google
search engine, for a billion Web pages can take several days.
Google currently ranks and searches 3 billion Web pages. Each
personalized or topic-sensitive ranking would require a separate
multi-day computation, but the payoff would be less time spent
wading through irrelevant search results. To speed up PageRank,
the Stanford team developed a trio of techniques in numerical
linear algebra ('extrapolation' methods, 'BlockRank,' and
'Adaptive PageRank.') "Further speed-ups are possible when we
use all these methods," Kamvar said. "Our preliminary
experiments show that combining the methods will m