[PageRank]

  There is an interesting rank, dudes! It's called

TrustRank

TrustRank is a link analysis technique described in a paper by Stanford University and Yahoo! researchers for semi-automatically separating useful webpages from spam.
 Many Web spam pages are created only with the intention of misleading search engines. 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 increase artificially 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.
 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.

http://en.wikipedia.org/wiki/TrustRank

[PageRank]

  And it's some additional info from a German website (pagerank.suchmaschinen-doktor.de) :

TrustRank algorithm

Introduction
The TrustRank algorithm is a procedure to rate the quality of websites. It was published by Gyongyi, Garcia-Molina and Pedersen 2004. The basic idea is similar to the PageRank algorithm - taking the linking structure to generate a measure for the quality of a page. The algorithm can be seen as a further development of the PageRank procedure. However, further development is not necessarily an improvement.

The starting point of the algorithm is the selection of good (trusted) pages by hand. These pages are the sources of trust. Trust can be transferred to other page by linking to them. Trust is propagating in the same was as PageRank. Additionally one can select sources of spam. The negative measure (inverse PageRank) is propagating backwards and is a measure for bad pages (spam). For the ranking algorithm both measures can be taken into account.

Mathematics


A simple variant of the TrustRank algorithm is given by

 TrustRank =  M-1 * X
where the matrix M (analogue to the PageRank algorithm) is given by
 M = 1 – d T
with
 Tij = 1 / Cj (if page j is linking to page i)
 Tij = 0 (otherwise)
d is a damping factor and X the source vector of the trust.

The inverse PageRank is given by

 Minv-1 * Xinv
with
 Minv = 1 –  dinv Tinv
The inverse transition matrix Tinv is definied by
 Tij = 1 / nj (if page i is linking to page  j)
 Tij = 0 (otherwise)
dinv is an additional damping factor, Xinv is the source vector of the spam (the bad pages) and nj ist he number of incoming links on page j. Minv is nether the transponent nor the inverse matrix of M.

In contrast to the normal transition matrix which is defined by incoming links, Tinv is a function of the outgoing links. Therefore, this measure for spam is propagating backwards. This means that pages are bad which are linking to bad pages. While good pages are defined as pages which have incoming links from good pages.

Search engine optimisation

 Search engine optimisation for TrustRank is the same as for PageRank. Additionally, one just has to ensure the pages are not considered as spam.


http://pagerank.suchmaschinen-doktor.de/trustrank.html

[MSL]

TrustRank checker

  Yes, it's important to know, when we're thinking about SEO. And are you interested in checking it (the TrustRank)? In case you are -- there is a TrustRank checker:

http://www.seomastering.com/trust-rank-checker.php

 

[Nguyen Van Tai]

SEOmoz is a very good test tools trust , I usually use it.