Berrar, Daniel, Hack, Catherine and Dubitzky, Werner (2005) Knowledge discovery in biology and biotechnology texts: a review of techniques, evaluation strategies, and applications. Critical reviews in biotechnology, 25 (1-2). pp. 31-52. [Journal article]
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Arguably, the richest source of knowledge (as opposed to fact and data collections) about biology and biotechnology is captured in natural-language documents such as technical reports, conference proceedings and research articles. The automatic exploitation of this rich knowledge base for decision making, hypothesis management (generation and testing) and knowledge discovery constitutes a formidable challenge. Recently, a set of technologies collectively referred to as knowledge discovery in text (KDT) has been advocated as a promising approach to tackle this challenge. KDT comprises three main tasks: information retrieval, information extraction and text mining. These tasks are the focus of much recent scientific research and many algorithms have been developed and applied to documents and text in biology and biotechnology. This article introduces the basic concepts of KDT, provides an overview of some of these efforts in the field of bioscience and biotechnology, and presents a framework of commonly used techniques for evaluating KDT methods, tools and systems.
|Item Type:||Journal article|
|Faculties and Schools:||Faculty of Life and Health Sciences > School of Biomedical Sciences|
Faculty of Life and Health Sciences
|Research Institutes and Groups:||Biomedical Sciences Research Institute > Genomic Medicine|
Biomedical Sciences Research Institute
|Deposited By:||Dr Catherine Hack|
|Deposited On:||23 Apr 2013 09:47|
|Last Modified:||23 Apr 2013 09:47|
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