Resumen
Online readers are in need of tools to help them cope with the mass of content available to the World-Wide Web. In traditional media, readers are provided assistance in making selections. This includes both implicit assistance in the form of editorial oversight and explicit assistance in the form of recommendation services such as movie reviews and restaurant guides. The electronic medium offers new opportunities to create recommendation services, ones that adapt over time to track their evolving interest. Fab is such a recommendation system. This article explains how a hybrid system can incorporate the advantages of both methods while inheriting the disadvantages. The authors describes the two approaches for content-based and collaborative recommendation, explain how a hybrid system can be created, and then describe Fab, an implementation of such a system. Fab is a distributed implementation of a hybrid system, and is part of the Stanford University digital library project.