A survey of formalisms for representing and reasoning with scientific knowledge

被引：14

作者：

Hunter, Anthony ^{[1
]}

Liu, Weiru ^{[2
]}

机构：

[1] UCL, Dept Comp Sci, London WC1E 6BT, England

[2] Queens Univ Belfast, Sch Elect Elect Engn & Comp Sci, Belfast BT9 5BN, Antrim, North Ireland

来源：

KNOWLEDGE ENGINEERING REVIEW | 2010年 / 25卷 / 02期

基金：

英国工程与自然科学研究理事会;

关键词：

INCOMPLETE STATISTICAL INFORMATION; LOGIC; ARGUMENTATION; SYSTEM; ONTOLOGIES; NETWORKS; INTEGRATION; MODELS;

D O I：

10.1017/S0269888910000019

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：199 / 222

页数：24