| 1. | Transforming the document shows the results of the default rules for white space stripping
对该文档的转换演示了应用空白去除的缺省规则的结果： |
| 2. | That is , a visual designer uses default rules to generate the value of a property
，也就是说，可视化设计器使用默认规则来生成属性( property )值。 |
| 3. | Applying this attribute to an assembly tells the obfuscation tool to use its default rules for the assembly type
将此属性应用到某一程序集会通知模糊处理工具对该程序集类型使用其默认规则。 |
| 4. | A rough set model to mine default rules was presented in order to reason and solve the decision question with incomplete information
摘要提出了一种基于粗集的缺省规则挖掘模型，以利于在信息不完备情况下进行推理和决策。 |
| 5. | Most fields are processed by the default rule , which copies the original data , but the date and quantity fields have special templates to reformat the date and to supply missing information , respectively
大部分字段都由默认规则处理，即复制原始数据，但是date和quantity字段有专门的模板，分别用于重新格式化日期和提供丢失的信息。 |
| 6. | A analytical theory is established by putting causal elements into partial states and actions , which deepens our understanding of event causation at the level of partial states and actions . ( 3 ) a causal rule representation is mapped into default logic formalism , based on the examination of general properties of causation . the default rule representation provides a concise syntactic and semantic formalism for potential causal relations to be used in causal reasoning models such as predicting , explaining and diagnosing
( 2 )通过对因果关系的可能类型的全面分析，给出了因果关系的结构与组成元素，特别是区分了潜在的因果关系内的原因、结果和因果场中的激活条件，并且把它们同半状态与动作对应起来，建立了关于因果关系的分析理论。 |
| 7. | In third part , we established two algorithm : data reduct and mdrbr ( mining default rules based on rough set ) , the objective is to acquire diagnostic knowledge from cases automatically from the diagnosed cases database , in the end established knowledge database that could be used for consequence . and in this part , we also discussed question how to inosculate between acquire knowledge by data mining and experience of clinician , and estimated for knowledge
从第三部分开始，在经典粗糙集理论的基础上建立适合于医学信息数据挖掘的算法:数据简约和默认规则挖掘算法mdrbr ( miningdefaultrulesbasedonroughset ) ，将诊断知识从确诊病例数据库中自动的获取出来，最终形成可用于推理的知识，还讨论了对于所挖掘到的知识如何与临床医生的经验融合的问题，以及知识的初步评价。 |
| 8. | There are follow innovative idea : solving the bottleneck problem in constructing medicinal assisted diagnosis system using technology of data mining ; starting with classical rough set theory , established two algorithms : data reduct and mdrbr ( mining default rules based on rough set ) , the objective is to acquire diagnostic knowledge from cases automatically from the diagnosed cases database , in the end established knowledge database that could be used for consequence
本研究的创新点:使用数据挖掘技术，解决医学辅助诊断专家系统开发过程中的瓶颈问题;从经典的粗糙集理论入手，结合确诊病例数据库和临床诊断的特点，得到两种数据挖掘算法:数据简约算法和默认规则挖掘算法mdrbr ( miningdefaultrulesbasedonroughset ) ，从已确诊病例数据库中获得骨肿瘤诊断知识，建立诊断知识库。 |
