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Searching for information in a hypertext medical handbook
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Artificial Intelligence in Medicine
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This paper attempts to provide a perspective from which to develop a more complete theory of information retrieval from hypertext documents. Viewing hypertexts as large information spaces, we compare two general classes of navigation methods, classes we call local and global. We argue that global methods necessitate some form of “index space” conceptually separate from the hypertext “document space”. We note that the architectures of both spaces effect the ease with which one can apply various information retrieval algorithms. We identify a number of different index space and document space architectures and we discuss some of the associated trade-offs between hypertext functionality and computational complexity. We show how some index space architectures can be exploited for enhanced information retrieval, query refinement, and automated reasoning. Through analysis of a number of prototype systems, we discuss current limitations and future potentials for various hypertext information retrieval structures.