distance: Compute distance

In LSAfun: Applied Latent Semantic Analysis (LSA) Functions

Compute distance

Description

Computes distance metrics for two single words

Usage

distance(x,y,method="euclidean",tvectors=tvectors)

Arguments

x	A single word, given as a character of length(x) = 1
y	A single word, given as a character of length(y) = 1
method	Specifies whether to compute euclidean or cityblock metric
tvectors	the semantic space in which the computation is to be done (a numeric matrix where every row is a word vector)

Details

Computes Minkowski metrics, i.e. geometric distances between the vectors for two given words. Possible options are euclidean for the Euclidean Distance, d(x,y) = \sqrt{\sum{(x-y)^2}}, and cityblock for the City Block metric, d(x,y) = \sum{|x-y|}

Value

The distance value as a numeric

Author(s)

Fritz Guenther

See Also

Cosine asym

Examples

data(wonderland)

distance("alice","rabbit",method="euclidean",tvectors=wonderland)

LSAfun documentation built on Nov. 18, 2023, 1:10 a.m.