@article{song2012video,
  abstract = {This paper considers the problem of web video geolocation: we hope to determine where on the Earth a web video was taken. By analyzing a 6.5-million geotagged web video dataset, we observe that there exist inherent geography intimacies between a video with its relevant videos (related videos and same-author videos). This social relationship supplies a direct and effective cue to locate the video to a particular region on the earth. Based on this observation, we propose an effective web video geolocation algorithm by propagating geotags among the web video social relationship graph. For the video that have no geotagged relevant videos, we aim to collect those geotagged relevant images that are content similar with the video (share some visual or textual information with the video) as the cue to infer the location of the video. The experiments have demonstrated the effectiveness of both methods, with the geolocation accuracy much better than state-of-the-art approaches. Finally, an online web video geolocation system: Video2Locatoin (V2L) is developed to provide public access to our algorithm.},
  author = {Song, Yi-Cheng and Zhang, Yong-Dong and Cao, Juan and Xia, Tian and Liu, Wu and Li, Jin-Tao},
  doi = {10.1109/TMM.2011.2172937},
  interhash = {090791b9f4e0737f35e40af91c4475d2},
  intrahash = {40d777e2e4a83e28c75a1c8ba0554153},
  issn = {1520-9210},
  journal = {Transactions on Multimedia},
  month = apr,
  number = 2,
  pages = {456--470},
  publisher = {IEEE},
  title = {Web Video Geolocation by Geotagged Social Resources},
  url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6054059},
  volume = 14,
  year = 2012
}

@inproceedings{fink2009geolocation,
  abstract = {Understanding the spatial distribution of people who author social media content is of growing interest for researchers and commerce. Blogging platforms depend on authors reporting their own location. However, not all authors report or reveal their location on their blog's home page. Automated geolocation strategies using IP address and domain name are not adequate for determining an author's location because most blogs are not self-hosted. In this paper we describe a method that uses the place name mentions in a blog to determine an author's location. We achieved an accuracy of 63% on a collection of 844 blogs with known locations.},
  author = {Fink, C. and Piatko, C. and Mayfield, J. and Chou, D. and Finin, T. and Martineau, J.},
  booktitle = {Proceedings of the International Conference on Computational Science and Engineering},
  doi = {10.1109/CSE.2009.584},
  interhash = {59b768c08026047c20d472ff93a4d513},
  intrahash = {70eddd59803db7efee4b8c840fe5a79b},
  month = aug,
  pages = {1088--1092},
  title = {The Geolocation of Web Logs from Textual Clues},
  url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5282996},
  volume = 4,
  year = 2009
}

@mastersthesis{flohr2011extraktion,
  abstract = {Informationen so aufzubereiten, dass sie für eine bestimmte Situation nützlich sind, ist eine große Herausforderung. In solchen Situationen soll ein Benutzer, wenn er sich an einem fremden Ort befindet, mit Hilfe des Android Smartphone interessante und wis- senswerte Informationen anzeigen lassen. Um dies bewerkstelligen zu können, muss es eine georeferenzierte Informationsquelle geben. Außerdem muss ein Konzept vor- handen sein, um diese Daten zu sammeln und so aufzubereiten, dass der Benutzer diese auch nützlich findet. Es muss eine Visualisierung dieser Daten geben, da der Platz zur Anzeige auf Smartphones sehr begrenzt ist. Als georeferenzierte Informationsquelle wird die Online-Enzyklopädie Wikipedia ge- nutzt, diese ist frei zugänglich und auch sehr umfassend. In dieser Arbeit wird das Konzept zur Sammlung und Aufbereitung von relevanten Daten behandelt. Zur In- formationsvisualisierung wird die Methode der Schlagwortwolke (engl. Tag-Cloud) verwendet.   It is a major challenge to prepare useful information for a particular situation. In this situation an Android smartphone user wants to display interesting and important facts about an unknown place. To manage this task existence of a geo-referenced source of information has to be ensured. In order to collect and prepare this data a creation of concept is needed. Due to limited display space, it is necessary to construct a suitable visualization of this data. Wikipedia is used as a geo-referenced information resource, because it has open-access and it offers global geo-referenced information. This thesis covers the concept of col- lecting and preparing relevant data. To visualize information a tag cloud is used.  },
  author = {Flohr, Oliver},
  interhash = {5d1f4da4964062ed6598fe8d8be8b591},
  intrahash = {a28959724af1907e7fc67a68e648c14c},
  month = aug,
  school = {Gottfried Wilhelm Leibniz Universität Hannover},
  title = {Extraktion und Visualisierung ortsbezogener Informationen mit Tag-Clouds},
  type = {bachelor thesis},
  url = {http://www.se.uni-hannover.de/pub/File/pdfpapers/Flohr2011a.pdf},
  year = 2011
}