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Detecting geographic locations from web resources

机译:从Web资源中检测地理位置

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The rapid pervasion of the web into users' daily lives has put much importance on capturing location-specific information on the web, due to the fact that most human activities occur locally around where a user is located. This is especially true in the increasingly popular mobile and local search environments. Thus, how to correctly and effectively detect geographic locations from web resources has become a key challenge to location-based web applications. In our previous work, we proposed to explicitly distinguish three types of locations for web resources, namely provider location, content location and serving location. Provider location is the physical location of the provider who owns the web resource; content location is the geographic location described in the web content; while serving location is the geographic scope that a web resource can reach. In this paper, we present a system that comprehensively employs a set of algorithms and different geographic sources by extracting geographic information from the web content, and mining hyperlink structures as well as user logs. As the result, only relevant geographic sources, rather than all of possible ones are used in computation of each category of web location. Finally, experimental results on large samples of web data show that our solution outperforms previous approaches.
机译:由于大多数人类活动在用户所在位置发生的事实,对用户日常生活中网络的快速疏忽对用户的快速渗透到用户的日常生活中的迅速迁移。在越来越受欢迎的移动和本地搜索环境中,这尤其如此。因此,如何正确和有效地检测来自Web资源的地理位置已经成为基于位置的Web应用程序的关键挑战。在我们以前的工作中,我们建议明确区分三种类型的Web资源,即提供者位置,内容位置和服务位置。提供商位置是拥有Web资源的提供商的物理位置;内容位置是Web内容中描述的地理位置;在服务位置的同时是Web资源可以达到的地理范围。在本文中,我们展示了一个系统,通过从Web内容中提取地理信息以及挖掘超链接结构以及用户日志来全面地使用一组算法和不同地理源。结果,只有相关的地理源,而不是所有可能的地理源都用于计算每个类别的网站位置。最后,在大型网络数据样本上的实验结果表明我们的解决方案优于先前的方法。

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