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  • × author_ss:"Smalheiser, N.R."
  • × language_ss:"e"
  • × theme_ss:"Computerlinguistik"
  1. Smalheiser, N.R.: Literature-based discovery : Beyond the ABCs (2012) 0.03
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    Abstract
    Literature-based discovery (LBD) refers to a particular type of text mining that seeks to identify nontrivial assertions that are implicit, and not explicitly stated, and that are detected by juxtaposing (generally a large body of) documents. In this review, I will provide a brief overview of LBD, both past and present, and will propose some new directions for the next decade. The prevalent ABC model is not "wrong"; however, it is only one of several different types of models that can contribute to the development of the next generation of LBD tools. Perhaps the most urgent need is to develop a series of objective literature-based interestingness measures, which can customize the output of LBD systems for different types of scientific investigations.