lsa: Latent Semantic Analysis

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.

AuthorFridolin Wild
Date of publication2015-05-08 19:58:09
MaintainerFridolin Wild <f.wild@open.ac.uk>
LicenseGPL (>= 2)
Version0.73.1

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Files in this package

lsa
lsa/tests
lsa/tests/lsa-tests.R
lsa/tests/polski.RData
lsa/NAMESPACE
lsa/demo
lsa/demo/lsa_landauer.R
lsa/demo/lsa_plot.R
lsa/demo/00Index
lsa/demo/lsa_essayscoring.R
lsa/data
lsa/data/corpus_scores.rda
lsa/data/specialchars.rda
lsa/data/stopwords_pl.rda
lsa/data/stopwords_ar.rda
lsa/data/stopwords_nl.rda
lsa/data/stopwords_en.rda
lsa/data/stopwords_de.rda
lsa/data/corpus_training.rda
lsa/data/corpus_essays.rda
lsa/data/alnumx.rda
lsa/data/stopwords_fr.rda
lsa/R
lsa/R/associate.R lsa/R/cosine.R lsa/R/query.R lsa/R/weightings.R lsa/R/triples.R lsa/R/textmatrix.R lsa/R/dimcalc.R lsa/R/sample.textmatrix.R lsa/R/lsa.R
lsa/MD5
lsa/DESCRIPTION
lsa/ChangeLog
lsa/man
lsa/man/textmatrix.Rd lsa/man/summary.textmatrix.Rd lsa/man/specialchars.Rd lsa/man/associate.Rd lsa/man/cosine.Rd lsa/man/corpora.Rd lsa/man/print.textmatrix.Rd lsa/man/triples.Rd lsa/man/weightings.Rd lsa/man/sample.textmatrix.Rd lsa/man/lsa.Rd lsa/man/as.textmatrix.Rd lsa/man/query.Rd lsa/man/dimcalc.Rd lsa/man/foldin.Rd lsa/man/alnumx.Rd lsa/man/stopwords.Rd

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