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LSAfun (version 0.7.1)

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

614

Version

0.7.1

License

GPL (>= 2)

Maintainer

Fritz Guenther

Last Published

November 17th, 2023

Functions in LSAfun (0.7.1)

multidocs

Comparison of sentence sets
conSIM

Similarity in Context
multicostring

Sentence x Vector Comparison
normalize

Normalize a vector
distance

Compute distance
neighbors

Find nearest neighbors
costring

Sentence Comparison
multicos

Vector x Vector Comparison
oldbooks

A collection of five classic books
genericSummary

Summarize a text
plausibility

Compute word (or compound) plausibility
plot_doclist

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

Pairwise cosine computation
syntest

A multiple choice test for synonyms and antonyms
wonderland

LSA Space: Alice's Adventures in Wonderland
plot_neighbors

2D- or 3D-Plot of neighbors
plot_wordlist

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

Simulated data for a Semantic Priming Experiment
coherence

Coherence of a text
SND

Semantic neighborhood density
MultipleChoice

Answers Multiple Choice Questions
asym

Asymmetric Similarity functions
Cosine

Compute cosine similarity
compose

Two-Word Composition
Predication

Compute Vector for Predicate-Argument-Expressions
LSAfun-package

Computations based on Latent Semantic Analysis
choose.target

Random Target Selection
analogy

Analogy