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The basic idea of latent semantic analysis (LSA) is, that text do have a higher order (=latent semantic) structure which, however, is obscured by word usage (e.g. through the use of synonyms or polysemy). By using conceptual indices that are derived statistically via a truncated singular value decomposition (a two-mode factor analysis) over a given document-term matrix, this variability problem can be overcome.

copied from cf-staging / r-lsa

Installers

Info: This package contains files in non-standard labels.
  • noarch v0.73.3
  • osx-64 v0.73.1
  • linux-64 v0.73.1
  • win-64 v0.73.1

conda install

To install this package run one of the following:
conda install conda-forge::r-lsa
conda install conda-forge/label/cf201901::r-lsa
conda install conda-forge/label/cf202003::r-lsa
conda install conda-forge/label/gcc7::r-lsa

Description


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