网页是组成互联网的基本数据单元，是各种面向互联网的应用系统最原始的数据源。网页内部含有大量噪音信息，如何从网页中有效地提取有价值的内容成为影响数据处理效果的关键。



网页正文提取指的是从原始网页中精确地提取出正文文本，比如提取新闻网页中的报道内容。能否高效地提取出网页的正文，是很多互联网应用系统如搜索引擎、新闻资讯系统等面临的一个重要问题。由于网页本身的无结构化的特点，通常采用的正文提取方法是针对目标网页的特点人工制定抽取模板，这类方法的优点是抽取精确，但其致命的缺点是模板建立和维护的工作量巨大，通用性和灵活性很差。



通过分析网页内部的链接分布特点，我们研制出了一种基于网页上下文链接密度的混合型正文判定算法，能够有效地解决上述通用提取方法的缺点，其最大特点是无须模板支持，因此不需要人工制定抽取和维护模板，将人工参与的工作量降到0。另外该方法具有很好的提取效果，对新闻网页的测试表明，该方法的准确率和召回率都在98％以上。

-Internet website is composed of the basic data units, is the Internet-oriented application system the most primitive data sources. Internal website contains a lot of noise information, from the website how to effectively extract the valuable contents of the data-processing become the key. Website text refers to the extraction from the original website accurately extracted the body text, such as news from the website as reporting. Can efficient extraction of the body of the website is that many Internet applications such as search engines, News and other information systems facing an important issue. As the website itself without structural characteristics, commonly used text extraction method is targeted website features developed from artificial template The advantages of these methods is