The World Wide Web contains
about 800 million webpages and that
number is increasing by the day. Finding
the right information becomes harder,
finding interesting sites might become
inpossible.
Try searching with AltaVista for websites about
"machine learning". You will
probably find over 4 million hits! Even
if you only try 1% of these and if you
would take 1 minute to visit one site, it
would take you about 8.5 months of
continuous surfing to visit them all...
What if you could use an
intelligent webbrowser that learns from
your surfing behaviour and could give you
advice about links on a certain website?
You can rely on its advice and only
follow the links your browser suggests.
This will surrely save you a lot of time
and frustration.
The Adaptive Webbrowser Case
shows how Machine Learning can be used to
develop a webbrowser that adapts itself
to its user and can give advice about the
interestingness of a website.
