# Predication: Compute Vector for Predicate-Argument-Expressions In codymarquart/LSAfun2: Applied Latent Semantic Analysis (LSA) Functions (no plotting/rgl)

## Description

Computes vectors for complex expressions of type PREDICATE[ARGUMENT] by applying the method of Kintsch (2001) (see Details).

## Usage

 `1` ```Predication(P,A,m,k,tvectors=tvectors,breakdown=TRUE,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 `k`-neighborhood; `k` ≤ `m` `tvectors` the semantic space in which the computation is to be done (a numeric matrix where every row is a word vector) `breakdown` if `TRUE`, the function `breakdown` is applied to the input `norm` whether to `normalize` the single word vectors before applying a composition function. Setting `norm = "none"` will not perform any normalizations, setting `norm = "all"` will normalize every involved word vector (Predicate, Argument, and every single activated neighbor). Setting `norm = "block"` will normalize the Argument vector and will normalize the [Predicate + neighbors] vector, to weight the Argument and the "Predicate in context" equally.

## 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

Fritz G?nther

## References

Kintsch, W. (2001). Predication. Cognitive science, 25, 173-202.

`cosine`, `neighbors`, `multicos`, `compose`
 ```1 2 3``` ```data(wonderland) Predication(P="mad",A="hatter",m=20,k=3,tvectors=wonderland) ```