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Google could be five times faster
By Winston Chai
Posted on May 27, 2003
Users of the Google search engine
like it because it's fast, but a team at Stanford University
has come up with ways to make it up to five times faster.
With the extra speed, Google could
be tailored for each user, according to the team. For
example, a sports-loving Google user looking for "tiger"
will see pages only on golfer Tiger Woods, not large
felines from Asia.
At present, Google's ranking system
relies on a method called PageRank, an invention of
co-founder Larry Page which calculates the popularity
and relevance of Web sites based on how many other sites
link to it.
"Computing PageRank for a billion
Web pages can take several days. Google currently ranks
and searches three billion Web pages and each personalized
or topic-sensitive ranking would also require a separate
multi-day computation," the university said in
a statement.
To speed up PageRank, Stanford researchers
have developed a trio of techniques based on a branch
of mathematics called numerical linear algebra. These
methods are described in three papers.
The first method from the Stanford
team, BlockRank, offers the most significant gain, speeding
up PageRank by three times, they claim.
The researchers make use of their
discovery that on most sites, up to 80 percent of links
point to other pages on the same site--each site looks
like a thick block of links.
PageRank processes each link individually,
but with their more efficient BlockRank method, these
same-site links are processed as a unit, before moving
on to links outside the site.
The second method involves the use
of extrapolation. Before scanning the Web, certain assumptions
about a site's importance are drawn up.
As the scanning continues, these
assumptions are either proven or disproved, with the
accuracy increasing as more links are processed. A site's
rank is extrapolated--guessed at--when a reasonable
amount of evidence is acquired. Compared with PageRank,
which only knows a site's rank after exhaustively trawling
the Web, extrapolation works 50 percent faster, say
the researchers.
The third method, called Adaptive
PageRank, relies on the fact that lower-ranking sites
tend to be computed faster than higher-ranking ones.
By dropping further processing of such quickly-computed
sites, a speed boost of up to 50 percent can be won,
they said.
While these methods have their individual
merits, the Stanford team believes they can offer even
greater returns when combined.
"Further speed-ups are possible
when we use all these methods," said Sepandar Kamvar,
one of the members of this project. "Our preliminary
experiments show that combining the methods will make
the computation of PageRank up to a factor of five faster.
"However, there are still several
issues to be solved. We're closer to a topic-based PageRank
than to a personalized ranking," he added.
The Stanford team's theories will
remain theories for now--they don’t appear to
have any official ties to Google itself.
"Google appreciates any contributions
that further the study of hyperlink analysis on the
web," was a spokesman's reply to CNETAsia when
asked whether Google will consider using the team's
methods, or if the privately-held company was involved
in the university team's efforts.
The Stanford team presented its paper
on these Google enhancements at the Twelfth Annual Word
Wide Web Conference in Budapest, Hungary, last week.
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