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LSAfun (version 0.6.2)

Applied Latent Semantic Analysis (LSA) Functions

Description

Provides functions that allow for convenient working with vector space models of semantics/distributional semantic models/word embeddings. Originally built for LSA models (hence the name), but can be used for all such vector-based models. For actually building a vector semantic space, use the package 'lsa' or other specialized software. Downloadable semantic spaces can be found at .

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Version

Install

install.packages('LSAfun')

Monthly Downloads

614

Version

0.6.2

License

GPL (>= 2)

Maintainer

Fritz Guenther

Last Published

May 1st, 2022

Functions in LSAfun (0.6.2)

compose

Two-Word Composition
coherence

Coherence of a text
Predication

Compute Vector for Predicate-Argument-Expressions
asym

Asymmetric Similarity functions
Cosine

Compute cosine similarity
choose.target

Random Target Selection
MultipleChoice

Answers Multiple Choice Questions
LSAfun-package

Computations based on Latent Semantic Analysis
conSIM

Similarity in Context
breakdown

Clean up special characters
neighbors

Find nearest neighbors
plot_neighbors

2D- or 3D-Plot of neighbors
normalize

Normalize a vector
plot_wordlist

2D- or 3D-Plot of a list of words
multicos

Vector x Vector Comparison
plot_doclist

2D- or 3D-Plot of a list of sentences/documents
genericSummary

Summarize a text
plausibility

Compute word (or compound) plausibility
oldbooks

A collection of five classic books
pairwise

Pairwise cosine computation
multicostring

Sentence x Vector Comparison
priming

Simulated data for a Semantic Priming Experiment
multidocs

Comparison of sentence sets
syntest

A multiple choice test for synonyms and antonyms
costring

Sentence Comparison
distance

Compute distance
wonderland

LSA Space: Alice's Adventures in Wonderland