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Latent semantic indexing (LSI) is a statistical technique for improving information retrieval effectiveness. Here, we use LSI to assist in literature-based discoveries. The idea behind literature-based discoveries is that different authors have already published certain underlying scientific ideas that, when taken together, can be connected to hypothesize a new discovery, and that these connections can be made by exploring the scientific literature. We explore latent semantic indexing's effectiveness on two discovery processes: uncovering "nearby" relationships that are necessary to initiate the literature based discovery process; and discovering more distant relationships that may genuinely generate new discovery hypotheses.
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Gordon et al. (1998) studied this question.
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