Adaptive web sites have been proposed to enhance ease of navigation and information retrieval. A variety of approaches are described in the literature, but consideration of interface presentation issues and realistic user studies are generally lacking. We report here a large-scale study of sites with dynamic information collections and user interests, where adaptation is based on an Ant Colony Optimization technique. We find that most users were able to locate information effectively without needing to perform explicit searches. The behavior of users who did search was similar to that on Internet search engines. Simulations based on site and user models give insight into the adaptive behavior and correspond to observations.

RightNow Web is an integrated software package for web-based customer service that has, at its core, a database of answers to frequently asked questions (FAQs). One major design goal is to facilitate end-user interaction with this dynamic document collection, i.e. make it as easy and efficient as possible for users to browse the collection and locate desired information. To this end, we perform several types of analysis on the session tracking database that records user navigation histories. First, using both explicit and implicit measures of user satisfaction, we infer a "solved count" representing the average utility of an FAQ. Second, using the user navigation patterns we construct a link matrix representing connections between FAQs. The technique of building up the link matrix and using it to advise users on related information amounts to a form of the "swarm intelligence" method of finding optimal paths. Both solved count and the link matrix are continuously updated as users interact with the site; furthermore, they are periodically "aged" to emphasize recent activity. The synergistic combination of these techniques allows users to learn from the database in a more effective manner, as evidenced by usage statistics.