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.

Documentation

Manual: lsa.pdf
Vignette: None available.

Maintainer: Fridolin Wild <f.wild at open.ac.uk>

Author(s): Fridolin Wild

Install package and any missing dependencies by running this line in your R console:

install.packages("lsa")

Depends SnowballC
Imports
Suggests tm
Enhances
Linking to
Reverse
depends
LSAfun, RWBP
Reverse
imports
DiffNet, IntClust
Reverse
suggests
Reverse
enhances
Reverse
linking to

Package lsa
Materials
URL
Task Views NaturalLanguageProcessing
Version 0.73.1
Published 2015-05-08
License GPL (>= 2)
BugReports
SystemRequirements
NeedsCompilation no
Citation
CRAN checks lsa check results
Package source lsa_0.73.1.tar.gz