FindMe systems originated in work I did with Kristian
Hammond when we were both at the Computer Science Department of the
University of Chicago. (He's now at Northwestern
University.) These systems use case-based reasoning as a way of
recommending products in e-commerce catalogs and provide critique-based
navigation as a primary user interface.
One interesting outcome of this work has been to emphasize the
complexity of the common-sense notion of similarity demanded by a user
of such catalogs as compared to the metrics used by many CBR systems.
The most famous FindMe system is the restaurant recommender Entree. Its restaurant database is circa 1996 so it isn't too useful as a practical tool anymore, but it still is an excellent demonstration of the idea.
The restaurant database underlying Entree and 3.5 years of user interaction data (~50,000 session) are available at the UC Irvine KDD archive.
There was a long period during which we were attempting to commercialize the FindMe idea. This period culminated in Verb, which ceased operation in June 2001.
Burke, R. Hybrid Recommender Systems: Survey and Experiments. User Modeling and User-Adapted Interaction. In Press. (PDF, 1.33M)
Burke, R. Knowledge-based Recommender Systems. In A. Kent (ed.), Encyclopedia of Library and Information Systems. Vol. 69, Supplement 32. New York: Marcel Dekker, 2000. (PDF, 911K)
Burke, R. Semantic Ratings and Heuristic Similarity for Collaborative Filtering. In AAAI Workshop on Knowledge-Based Electronic Markets, pages 14-20. AAAI, 2000. (PDF, 163K)
Burke, R. The Wasabi Personal Shopper: A Case-Based Recommender System. In Proceedings of the 11th National Conference on Innovative Applications of Artificial Intelligence, pages 844-849, AAAI, 1999. (PDF, 59K)
Burke, R., Hammond, K., and Young, B. The FindMe Approach to Assisted Browsing. IEEE Expert, 12(4), pages 32-40, 1997. (Postscript, 199K, no figures, though)
Burke, R., Hammond, K. & Cooper, E. Knowledge-based navigation of complex information spaces. In Proceedings of the 13th National Conference on Artificial Intelligence, pages 462-468, AAAI, 1996. (PDF, 219K)