  It is shown that personalization of web content can be advantageously viewed
as a form of partial evaluation --- a technique well known in the programming
languages community. The basic idea is to model a recommendation space as a
program, then partially evaluate this program with respect to user preferences
(and features) to obtain specialized content. This technique supports both
content-based and collaborative approaches, and is applicable to a range of
applications that require automatic information integration from multiple web
sources. The effectiveness of this methodology is illustrated by two example
applications --- (i) personalizing content for visitors to the Blacksburg
Electronic Village (http://www.bev.net), and (ii) locating and selecting
scientific software on the Internet. The scalability of this technique is
demonstrated by its ability to interface with online web ontologies that index
thousands of web pages.
