A survey of formalisms for representing and reasoning with scientific knowledge.
KNOWL ENG REV
199 - 222.
With the rapid growth in the quantity and complexity of scientific knowledge available for scientists, and allied professionals, the problems associated with harnessing this knowledge are well recognized. Some of these problems are a result of the uncertainties and inconsistencies that arise in this knowledge. Other problems arise from heterogeneous and informal formats for this knowledge. To address these problems, developments in the application of knowledge representation and reasoning technologies can allow scientific knowledge to be captured in logic-based formalisms. Using such formalisms, we can undertake reasoning with the uncertainty and inconsistency to allow automated techniques to be used for querying and combining of scientific knowledge. Furthermore, by harnessing background knowledge, the querying and combining tasks can be carried out more intelligently. In this paper, we review some of the significant proposals for formalisms for representing and reasoning with scientific knowledge.
|Title:||A survey of formalisms for representing and reasoning with scientific knowledge|
|Keywords:||INCOMPLETE STATISTICAL INFORMATION, BIOLOGICAL NETWORKS, ARTIFICIAL-INTELLIGENCE, MERGING OPERATORS, GENETIC NETWORKS, CLINICAL-TRIALS, LOGIC, ARGUMENTATION, SYSTEM, ONTOLOGIES|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Computer Science
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