Welcome to the WebWatcher Project
Overview
WebWatcher is a "tour guide" agent for the world wide web.
Once you tell it what kind of information you seek, it accompanies you
from page to page as you browse the web, highlighting hyperlinks that
it believes will be of interest. Its strategy for giving advice is
learned from feedback from earlier tours.
WebWatcher Instances
WebWatcher can help you search for information starting from any of
the following pages, but it has learned the most for the first of
these. Currently WebWatcher is online only on an irregular basis. You
might want to take a look at the following demo instead.
Personal WebWatcher
WebWatcher gives tours to many people (over 8,500 thus far), and
learns to become a specialist at a particular web site. In contrast,
our
Personal WebWatcher project stays with a single user, becoming a
specialist in that user's interests.
Publications
- WebWatcher: A Tour Guide for the
World Wide Web , T. Joachims, D. Freitag, T. Mitchell,
Proceedings of IJCAI97, August 1997 (longer
version internal CMU technical report September 1996).
Abstract: We describe WebWatcher as a tour guide agent for the
web, the learning algorithms used by WebWatcher, experimental results
based on learning from thousands of users, and lessons learned from
this case study of tour guide agents.
- WebWatcher: A Learning Apprentice for the World Wide Web , in the 1995 AAAI Spring Symposium on Information Gathering from Heterogeneous, Distributed Environments, Stanford, March 1995.
Abstract: A description of WebWatcher and a comparison of different machine learning approaches to suggest hyperlinks.
- WebWatcher: Machine Learning and Hypertext, Fachgruppentreffen Maschinelles Lernen, Dortmund, Germany, August 1995.
Abstract: A description of how hypertext structure can be used to cluster WWW pages.
Project Members
Alumni:
- Robert Armstrong
- Ada Lee
- Shannon Mitchell
- David "Stork" Zabowski
Please report bugs and comments to webwatch@cs.cmu.edu.