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Building Location Embeddings from Physical Trajectories and Textual Representations

Biester, Laura; Banea, Carmen; Mihalcea, Rada


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{
  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  }, 
  "description": "<p>Code for building and evaluating location embeddings for the 2020 AACL-IJCNLP&nbsp;paper &quot;Building Location Embeddings from Physical Trajectories and Textual Representations.&quot;</p>\n\n<p><strong>Abstract:&nbsp;</strong>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&#39;s area of study to a student&#39;s depression level, showing the effectiveness of these location embeddings.</p>\n\n<p><strong>Contact:</strong>&nbsp;Please contact Laura Biester (lbiester@umich.edu) with questions.</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "University of Michigan", 
      "@id": "https://orcid.org/0000-0003-3901-2968", 
      "@type": "Person", 
      "name": "Biester, Laura"
    }, 
    {
      "affiliation": "University of Michigan", 
      "@type": "Person", 
      "name": "Banea, Carmen"
    }, 
    {
      "affiliation": "University of Michiagn", 
      "@type": "Person", 
      "name": "Mihalcea, Rada"
    }
  ], 
  "url": "https://zenodo.org/record/4479440", 
  "datePublished": "2020-12-04", 
  "@type": "SoftwareSourceCode", 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.4479440", 
  "@id": "https://doi.org/10.5281/zenodo.4479440", 
  "workFeatured": {
    "url": "http://aacl2020.org/", 
    "alternateName": "AACL-IJCNLP 2020", 
    "location": "Virtual", 
    "@type": "Event", 
    "name": "1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing"
  }, 
  "name": "Building Location Embeddings from Physical Trajectories and Textual Representations"
}
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