Geotagging Named Entities in Web Pages

• Author / Creator

  Yu, Jiangwei

• We study the problem of geotagging named entities where the goal is to identify
  the most relevant location of a named entity based on the content of the Web pages
  where the entity is mentioned. We hypothesize the relationship between the mentions
  of an entity and its geo-center in web pages, and propose a framework that
  explores this hypothesis and provides a model that can give a ranked list of locations
  at different location granularities for an entity. We further study the problem
  of dispersion, and show that the dispersion of a name can be estimated and a geo-center
  can be detected at an exact dispersion level.
  Two key features of our approach are: (i) minimal assumption is made on the
  structure of the mentions hence the approach can be applied to a diverse and heterogeneous
  set of web pages, and (ii) the approach is unsupervised, leveraging shallow
  English linguistic features and large gazetteers.
  We evaluate our methods under different settings and with different categories
  of named entities. Our evaluation reveals that the geo-center of a name can be
  estimated with a good accuracy based on some simple statistics of the mentions,
  and that the accuracy of the estimation varies with the categories of the names.

• Subjects / Keywords

  • Probabilistic models
  • Locations
  • Geotagging
  • Named entities
  • Location extraction
  • Location ranking
  • Unsupervised framework
  • Geo-center

• Graduation date

  Fall 2014

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R3DR2PG3X

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.