Online Advertising
TrustRank
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From Wikipedia the free encyclopedia.
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TrustRank is a new technique proposed by Zoltán Gyöngyi and
Hector Garcia-Molina of Stanford University and Jan Pedersen of Yahoo!
to semi-automatically separate reputable, good pages from
spam.
Many Web spam pages are only created with the intention of misleading
search engines. See also
Spamdexing.
These pages, chiefly created for commercial reasons, use various techniques to
achieve higher-than-deserved rankings on the search engines' result pages. While
human experts can easily identify spam, it is too expensive to manually evaluate
a large number of pages.
One popular method for improving rankings is to artificially increase the
perceived importance of a document through complex linking schemes.
Google's
PageRank
and similar methods for determining the relative importance of Web documents
have been subjected to manipulation.
The TrustRank method calls for selecting a small set of seed pages to be
evaluated by an expert. Once the reputable seed pages are manually identified, a
crawl extending outward from the seed set seeks out similarly reliable and
trustworthy pages. TrustRank's reliability diminishes as documents become
further removed from the seed set.
The researchers who proposed the TrustRank methodology have continued to
refine their work by evaluating related topics, such as measuring
spam mass.
External links
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