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Information Extraction Using Web Usage Mining, Web Scrapping and Semantic Annotation

机译:使用Web使用情况挖掘,Web爬取和语义注释的信息提取

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Extracting useful information from the web is the most significant issue of concern for the realization of semantic web. This may be achieved by several ways among which Web Usage Mining, Web Scrapping and Semantic Annotation plays an important role. Web mining enables to find out the relevant results from the web and is used to extract meaningful information from the discovery patterns kept back in the servers. Web usage mining is a type of web mining which mines the information of access routes/manners of users visiting the web sites. Web scraping, another technique, is a process of extracting useful information from HTML pages which may be implemented using a scripting language known as Prolog Server Pages(PSP) based on Prolog. Third, Semantic annotation is a technique which makes it possible to add semantics and a formal structure to unstructured textual documents, an important aspect in semantic information extraction which may be performed by a tool known as KIM(Knowledge Information Management). In this paper, we revisit, explore and discuss some information extraction techniques on web like web usage mining, web scrapping and semantic annotation for a better or efficient information extraction on the web illustrated with examples.
机译:从网络中提取有用的信息是实现语义网络最重要的问题。这可以通过多种方法来实现,其中Web用法挖掘,Web废弃和语义注释起着重要的作用。 Web挖掘使能够从Web上找到相关结果,并用于从保留在服务器中的发现模式中提取有意义的信息。 Web使用挖掘是一种Web挖掘,它挖掘访问网站的用户的访问路线/方式的信息。 Web抓取是另一种技术,它是从HTML页面提取有用信息的过程,可以使用基于Prolog的称为Prolog服务器页面(PSP)的脚本语言来实现。第三,语义注释是一种可以为非结构化文本文档添加语义和形式结构的技术,这是语义信息提取的重要方面,可以通过称为KIM(知识信息管理)的工具来执行。在本文中,我们将重新审视,探索和讨论一些Web上的信息提取技术,例如Web用法挖掘,Web抓取和语义标注,以在示例中说明更好或更有效的Web信息提取。

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