WebWatcher: A Tour Guide for the World Wide Web

Abstract

We explore the notion of a tour guide software agent for assisting users browsing the World Wide Web. A Web tour guide agent provides assistance similar to that provided by a human tour guide in a museum — it guides the user along an appropriate path through the collection, based on its knowledge of the user’s interests, of the location and relevance of various items in the collection, and of the way in which others have interacted with the collection in the past. This paper describes a simple but operational tour guide, called WebWatcher, which has given over 5000 tours to people browsing CMU’s School of Computer Science Web pages. WebWatcher accompanies users from page to page, suggests appropriate hyperlinks, and learns from experience to improve its advice-giving skills. We describe the learning algorithms used byWebWatcher, experimental results showing their effectiveness, and lessons learned from this case study in Web tour guide agents.