The PageRank algorithm used by google harnesses the implicit collective
intelligence present in the structure of the world wide web. Any page on
the Internet will generally link to at least one other, by modelling this
link structure as a graph, we can build up a symbolic representation of
the world wide web.

As the basic level, the nodes with the highest degrees can be considered
the most "popular" and by inference the most important - which can be used
to rank the pages when returning search results.

Expanding on this theory, we can then say that the links from an important
pages are themselves more important. Using this idea we can adjust the
rankings of our pages so that pages linked to be the most important pages
are considered more relevant.

The actual Google PageRank algorithm is much more complex than this, but
follows the same underlying principles. It incorporates some more advanced
reasoning to avoid website creators exploiting their knowledge of the algorithm
to artificially increase their PageRank through use of web-rings and other
similar reciprocal hyperlinking schemes.