User-adaptive (or "personalized") systems take individual character-
istics of their current users into account and adapt their behavior ac-
cordingly. Several empirical studies demonstrate their benefits in areas
like education and training, online help for complex software, dynamic
information delivery, provision of computer access to people with dis-
abilities, and to some extent information retrieval. Recently, personal-
ized systems have also started to appear on the World Wide Web where
they are primarily used for customer relationship management. The aim
hereby is to provide value to customers by serving them as individuals
and by offering them a unique personal relationship with the business.
Studies show that web visitors indeed spend considerably more time at
personalized than at regular portals and view considerably more web
pages. Personalized sites in general also draw more visitors and turn
more visitors into buyers. Personalization therefore would look like a
win-win technology for both consumers and online businesses. However, it
has a major down- side: in order to be able to exhibit personalized
behavior, user-adaptive systems have to collect considerable amounts of
personal data and "lay them in stock" for possible future usage.
Moreover, the collection of information about the user is often
performed in a relatively inconspic- uous manner (such as by monitoring
users' web navigation behavior), in order not to distract users from
their tasks.