The key problem in information extraction is how to generate accurate, general, and robust extraction rules.
信息抽取中的关键问题是如何编写健壮、准确和通用的抽取规则。
Rather than relying on automatically recorded hidden field data, extraction rules can be manually added and customized as needed.
提取规则可以根据需要手动添加和自定义，而不是依赖于自动记录的隐藏字段数据。
With standard XSLT, we can exploit strong and flexible features of the language to construct simple, robust and general extraction rules.
基于标准的XSLT，可以利用它强大而且灵活的特性编写简单、健壮和通用的抽取规则。
At last, this paper studied the optimization of extraction rules and compared several information location methods. The aim is to generate simple, robust and general extraction rules.
最后，本文还对提取规则的优化问题进行了研究，对几种信息定位方式进行了比较，目的是此基础上编写更为简单、健壮和通用的提取规则。
There are two parts in the system, the definition of the Extraction rules and the execution of the Extraction rules.
系统主要分为两个部分，抽取规则的定义阶段以及抽取规则的执行阶段。
There are two main routes in the study area of information extraction: rules-based model and statistics-based model.
在信息抽取的研究领域，有两条主要的技术路线：基于规则的路线与基于统计模型的路线。
There are two main routes in the study area of information extraction: rules-based model and statistics-based model.
在信息抽取的研究领域，有两条主要的技术路线：基于规则的路线与基于统计模型的路线。
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