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Building Location Embeddings from Physical Trajectories and Textual Representations

Biester, Laura; Banea, Carmen; Mihalcea, Rada


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  <dc:creator>Biester, Laura</dc:creator>
  <dc:creator>Banea, Carmen</dc:creator>
  <dc:creator>Mihalcea, Rada</dc:creator>
  <dc:date>2020-12-04</dc:date>
  <dc:description>Code for building and evaluating location embeddings for the 2020 AACL-IJCNLP paper "Building Location Embeddings from Physical Trajectories and Textual Representations."

Abstract: Word embedding methods have become the de-facto way to represent words, having been successfully applied to a wide array of natural language processing tasks. In this paper, we explore the hypothesis that embedding methods can also be effectively used to represent spatial locations. Using a new dataset consisting of the location trajectories of 729 students over a seven month period and text data related to those locations, we implement several strategies to create location embeddings, which we then use to create embeddings of the sequences of locations a student has visited. To identify the surface level properties captured in the representations, we propose a number of probing tasks such as the presence of a specific location in a sequence or the type of activities that take place at a location. We then leverage the representations we generated and employ them in more complex downstream tasks ranging from predicting a student's area of study to a student's depression level, showing the effectiveness of these location embeddings.

Contact: Please contact Laura Biester (lbiester@umich.edu) with questions.</dc:description>
  <dc:identifier>https://zenodo.org/record/4479440</dc:identifier>
  <dc:identifier>10.5281/zenodo.4479440</dc:identifier>
  <dc:identifier>oai:zenodo.org:4479440</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>url:https://www.aclweb.org/anthology/2020.aacl-main.44/</dc:relation>
  <dc:relation>doi:10.5281/zenodo.4479439</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:title>Building Location Embeddings from Physical Trajectories and Textual Representations</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>software</dc:type>
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