@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
}

@inproceedings{tezuka2001webbased,
  abstract = {Dealing with prepositions such as "near", "between" and "in front of" is very important in geographic information systems (GISs). In most systems, real-world distances are used to handle these prepositions. One of the difficulties in processing these prepositions lies in the fact that their geographical range is distorted in people's cognitive maps. For example, the size of an area referred to by the preposition "near" gets narrowed when a more famous landmark exists right next to the base geographical object. This is because users are likely to choose the most famous landmark when referring to a certain position. Also, the area referred to by "between" is not a straight line; it curves along the most commonly used pathway between the base objects. The difference in the popularity of geographical objects is the main reason for causing such distortions in cognitive maps. Since there is a large amount of data on the World Wide Web, we believe that such conceptual distortion can be calculated by analyzing Web data. Popularity and co-occurrence rates are calculated through their frequency in Web resources. Inference rules are set to restrict the target of conceptual prepositions using GISs and information obtained from the Web},
  author = {Tezuka, T. and Lee, Ryong and Kambayashi, Y. and Takakura, H.},
  booktitle = {Proceedings of the Second International Conference on Web Information Systems Engineering},
  doi = {10.1109/WISE.2001.996692},
  interhash = {132a7e8b5e47313ce56c790188d4d384},
  intrahash = {b5b4d65538c9253a2b43c6252521d4f4},
  month = dec,
  pages = {14--21},
  title = {Web-based inference rules for processing conceptual geographical relationships},
  url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=996692&tag=1},
  volume = 2,
  year = 2001
}