Document geolocation using language models built from lexical and geographic similarity

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Document geolocation using language models built from lexical and geographic similarity

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Title: Document geolocation using language models built from lexical and geographic similarity
Author: Skiles, Erik David
Abstract: This thesis investigates the automatic identification of the location of doc- uments. This process of geolocation aids in toponym resolution, document summarization, and geographic-based marketing. I focus on minimally su- pervised methods to examine both the lexical similarities and the geographic similarities between documents. This method predicts the location of a doc- ument as a single point on the earth’s surface. Three data sets are used to evaluate this method: a set of geotagged Wikipedia articles and two sets of Twitter feeds. For Wikipedia, the combined method obtains a median error of 12.1 kilometers and an improvement in mean error to 164 kilometers. The large Twitter data shows the greatest improvement from this method with a median error of 333 kilometers, down from the previous best of 463 kilometers.
Department: Linguistics
Subject: Geolocation
URI: http://hdl.handle.net/2152/ETD-UT-2012-05-5717
Date: 2012-05

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