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.