Literature Based Discovery: Beyond the ABCs

Abstract

Literature based discovery (LBD) refers to a particular type of text mining that seeks to identify non-trivial assertions that are implicit, and not explicitly stated, that are detected by juxtaposing (generally a large body of) documents. In this review, I will provide a brief overview of the past and present of literature based discovery, and will propose some new directions for the next decade. The prevalent A-B-C 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.