Predication {LSAfun} | R Documentation |
Compute Vector for Predicate-Argument-Expressions
Description
Computes vectors for complex expressions of type PREDICATE[ARGUMENT] by applying the method of Kintsch (2001) (see Details).
Usage
Predication(P,A,m,k,tvectors=tvectors,norm="none")
Arguments
P |
Predicate of the expression, a single word (character vector) |
A |
Argument of the expression, a single word (character vector) |
m |
number of nearest words to the Predicate that are initially activated |
k |
size of the |
tvectors |
the semantic space in which the computation is to be done (a numeric matrix where every row is a word vector) |
norm |
whether to |
Details
The vector for the expression is computed following the Predication Process by Kintsch (2001):
The m
nearest neighbors to the Predicate are computed. Of those, the k
nearest neighbors to
the Argument are selected. The vector for the expression is then computed as the sum of
Predicate vector, Argument vector, and the vectors of those k
neighbors (the k
-neighborhood).
Value
An object of class Pred
: This object is a list consisting of:
$PA |
The vector for the complex expression as described above |
$P.Pred |
The vector for Predicate plus the k-neighborhoodvectors without the Argument vector |
$neighbors |
The words in the k-neighborhood. |
$P |
The Predicate given as input |
$A |
The Argument given as input |
Author(s)
Fritz Guenther
References
Kintsch, W. (2001). Predication. Cognitive Science, 25, 173-202.
See Also
cosine
,
neighbors
,
multicos
,
compose
Examples
data(wonderland)
Predication(P="mad",A="hatter",m=20,k=3,tvectors=wonderland)