Automated Index Generation for Constructing Large-Scale Conversational Hypermedia Systems

Richard Osgood, Ray Bareiss

At the Institute for the Learning Sciences we have been developing large scale hypermedia systems, called ASK systems, that are designed to simulate aspects of conversations with experts. They provide access to manually indexed, multimedia databases of story units. We are particularly concerned with finding a practical solution to the problem of finding indices for thes units when the database grows too large for manual techniques. Our solution is to provide automated assistance that proposes relative links between units, eliminating the need for manual unit-to-unit comparison. In this paper we describe eight classes of links, and show a representation and inference procedure to assist in locating instances of each.


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