Geographic focus detection using multiple location taggers

Philipp Berger, Patrick Hennig, Dustin Glaeser, Hauke Klement, C. Meinel
{"title":"Geographic focus detection using multiple location taggers","authors":"Philipp Berger, Patrick Hennig, Dustin Glaeser, Hauke Klement, C. Meinel","doi":"10.1109/ASONAM.2014.6921618","DOIUrl":null,"url":null,"abstract":"Being able to identify locations associated to a Web resource is essential for providing location-based Web applications. However, geographical information in Web documents is rarely supplied in a machine-readable way and therefore not easily discoverable. As a consequence, it is necessary to extract geographical keywords from Web documents and to associate locations with them. This method is called location tagging. In this paper we present a location tagging approach for unstructured documents which utilizes multiple external location providers. Detected locations are ranked according to their relevance for the document, in order to identify a document's geographical focus, which is its most representative location. We present an exemplary implementation of our proposed approach using two location providers and evaluate our method's applicability.","PeriodicalId":143584,"journal":{"name":"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASONAM.2014.6921618","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Being able to identify locations associated to a Web resource is essential for providing location-based Web applications. However, geographical information in Web documents is rarely supplied in a machine-readable way and therefore not easily discoverable. As a consequence, it is necessary to extract geographical keywords from Web documents and to associate locations with them. This method is called location tagging. In this paper we present a location tagging approach for unstructured documents which utilizes multiple external location providers. Detected locations are ranked according to their relevance for the document, in order to identify a document's geographical focus, which is its most representative location. We present an exemplary implementation of our proposed approach using two location providers and evaluate our method's applicability.
使用多个位置标记器进行地理焦点检测
能够识别与Web资源相关联的位置对于提供基于位置的Web应用程序至关重要。但是,Web文档中的地理信息很少以机器可读的方式提供,因此不容易发现。因此,有必要从Web文档中提取地理关键字,并将位置与其关联起来。这种方法称为位置标记。在本文中,我们提出了一种利用多个外部位置提供者的非结构化文档位置标记方法。检测到的位置根据其与文档的相关性进行排序,以确定文档的地理焦点,这是其最具代表性的位置。我们提出了一个使用两个位置提供程序的示例性实现,并评估了我们方法的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信