J. Shavlik, S. Calcari, T. Eliassi-Rad & J. Solock (1999).
An Instructable, Adaptive Interface for Discovering and Monitoring Information on the World-Wide Web. Proceedings of the 1999 International Conference on Intelligent User Interfaces, pp. 157 - 160, Redondo Beach, CA.

This publication is available in PDF and available in postscript.

Abstract:

We are creating a customizable, intelligent interface to the World-Wide Web that assists a user in locating specific, current, and relevant information. The Wisconsin Adaptive Web Assistant (WAWA) is capable of accepting instructions regarding what type of information the users are seeking and how to go about looking for it. WAWA compiles these instructions into neural networks, which means that the system's behavior can be modified via training examples. Users can create these training examples by rating pages retrieved by WAWA, but more importantly the system uses techniques from reinforcement learning to internally create its own examples (users can also later provide additional instructions). WAWA uses these neural networks to guide its autonomous navigation of the Web, thereby producing an interface to the Web that users periodically instruct and which in the background searches the Web for relevant information, including periodically revisiting pages that change regularly.

Return to the publications of the Univ. of Wisconsin Machine Learning Research Group.