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LSAfun (version 0.8.1)

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

463

Version

0.8.1

License

GPL (>= 2)

Maintainer

Fritz Guenther

Last Published

April 2nd, 2025

Functions in LSAfun (0.8.1)

conSIM

Similarity in Context
distance

Compute distance
neighbors

Find nearest neighbors
multicos

Vector x Vector Comparison
compose

Two-Word Composition
costring

Sentence Comparison
plot_neighbors

2D- or 3D-Plot of neighbors
oldbooks

A collection of five classic books
normalize

Normalize a vector
plausibility

Compute word (or compound) plausibility
plot_doclist

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

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

Pairwise cosine computation
wonderland

LSA Space: Alice's Adventures in Wonderland
priming

Simulated data for a Semantic Priming Experiment
syntest

A multiple choice test for synonyms and antonyms
Predication

Compute Vector for Predicate-Argument-Expressions
SND

Semantic neighborhood density
asym

Asymmetric Similarity functions
LSAfun-package

Computations based on Latent Semantic Analysis
coherence

Coherence of a text
choose.target

Random Target Selection
MultipleChoice

Answers Multiple Choice Questions
Cosine

Compute cosine similarity
analogy

Analogy
centroid_analysis

Centroid Analysis
genericSummary

Summarize a text
multicostring

Sentence x Vector Comparison
multidocs

Comparison of sentence sets