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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.

Type Size Name Uploaded Downloads Labels
conda 213.4 kB | noarch/r-lsa-0.73.3-r43h142f84f_0.tar.bz2  1 year and 1 month ago 26 main
conda 214.2 kB | noarch/r-lsa-0.73.3-r42h142f84f_0.tar.bz2  2 years and 8 months ago 77 main
conda 213.7 kB | noarch/r-lsa-0.73.1-r36h6115d3f_0.tar.bz2  5 years and 1 day ago 117 main

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