A Semantic Scraping Model for Web Resources - Applying Linked Data to Web Page Screen Scraping

A Semantic Scraping Model for Web Resources - Applying Linked Data to Web Page Screen Scraping
复制标题

DOI:
--
复制
发表时间:
2011
期刊:
--
影响因子:
--
通讯作者:
José Ignacio Fernández-Villamor;Jacobo Blasco-García;C. Á. Iglesias;M. Garijo
José Ignacio Fernández-Villamor;Jacobo Blasco-García;C. Á. Iglesias;M. Garijo
中科院分区:
其他
文献类型:
--
作者:
José Ignacio Fernández-Villamor;Jacobo Blasco-García;C. Á. Iglesias;M. Garijo

文献摘要

被引文献

相似文献

尽管语义Web设施的出现越来越多,但Internet中只有有限数量的可用资源提供语义访问。最近的创举,如新兴的关联数据网,通过使用不同的技术(如数据库-语义映射和抓取)将现有资源移植到语义网,提供对可用数据的语义访问。然而,现有的刮刀解决方案是基于特别的解决方案,辅以图形界面来加速刮刀的开发。本文提出了一种基于语义技术的网页抓取通用框架。该框架分为三个层次:抓取服务、语义抓取模型和语法抓取。第一层提供了通用应用程序或智能代理的接口,用于在高层上从web收集信息。第二层定义了抓取过程的语义RDF模型,以便为抓取任务提供声明性方法。最后,第三层提供了针对特定技术的RDF抓取模型的实现。这项工作已经在一个场景中得到验证,该场景演示了它在mashup技术中的应用。
In spite of the increasing presence of Semantic Web Facilities, only a limited amount of the available resources in the Internet provide a semantic access. Recent initiatives such as the emerging Linked Data Web are providing semantic access to available data by porting existing resources to the semantic web using different technologies, such as database-semantic mapping and scraping. Nevertheless, existing scraping solutions are based on ad-hoc solutions complemented with graphical interfaces for speeding up the scraper development. This article proposes a generic framework for web scraping based on semantic technologies. This framework is structured in three levels: scraping services, semantic scraping model and syntactic scraping. The first level provides an interface to generic applications or intelligent agents for gathering information from the web at a high level. The second level defines a semantic RDF model of the scraping process, in order to provide a declarative approach to the scraping task. Finally, the third level provides an implementation of the RDF scraping model for specific technologies. The work has been validated in a scenario that illustrates its application to mashup technologies.