Dataset Open Access

Hathi Trust Library Vectorized features

Benjamin M. Schmidt


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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Benjamin M. Schmidt</dc:creator>
  <dc:date>2018-09-21</dc:date>
  <dc:description>A smaller-resolution (and therefore more portable) version of the Stable Random Projection Hathi Trust features described in my forthcoming article. The Northeastern repository is many individual files with 1280 random dimensions; this is just 640 random dimensions. The numbers are also experimentally encoded as half-precision floats, which cuts the file size by half at the cost of only being supported by my Python module. The net result is a file 1/4 the size of the full resolution ones for the paper that has, probably, something like 60-80% of the information content.

The full file is 'ht-640d-complete-half-precision.bin'. You can also download 11 smaller files organized by language.

Code to read these files is at https://github.com/bmschmidt/pySRP. </dc:description>
  <dc:identifier>https://zenodo.org/record/1424831</dc:identifier>
  <dc:identifier>10.5281/zenodo.1424831</dc:identifier>
  <dc:identifier>oai:zenodo.org:1424831</dc:identifier>
  <dc:relation>doi:10.5281/zenodo.1424830</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>Dimensionality reduction</dc:subject>
  <dc:subject>Digital Libraries</dc:subject>
  <dc:subject>Digital humanities</dc:subject>
  <dc:title>Hathi Trust Library Vectorized features</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>dataset</dc:type>
</oai_dc:dc>
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