Description Usage Arguments Details Value Author(s) References See Also Examples

Computes the vector of a complex expression p consisting of two single words u and v,
following the methods examined in Mitchell & Lapata (2008) (see *Details*).

1 2 3 |

`x` |
a single word (character vector with |

`y` |
a single word (character vector with |

`a,b,c` |
weighting parameters, see |

`m` |
number of nearest words to the Predicate that are initially activated (see |

`k` |
size of the |

`lambda` |
dilation parameter for |

`method` |
the composition method to be used (see |

`norm` |
whether to |

`tvectors` |
the semantic space in which the computation is to be done (a numeric matrix where every row is a word vector) |

`breakdown` |
if |

Let *p* be the vector with entries *p_i* for the two-word phrase consisiting of *u* with entries *u_i* and *v* with entries *v_i*.
The different composition methods as described by Mitchell & Lapata (2008, 2010) are as follows:

Additive Model (

`method = "Add"`

)*p_i = u_i + v_i*Weighted Additive Model (

`method = "WeightAdd"`

)*p_i = a*u_i + b*v_i*Multiplicative Model (

`method = "Multiply"`

)*p_i = u_i * v_i*Combined Model (

`method = "Combined"`

)*p_i = a*u_i + b*v_i + c*u_i*v_i*Predication (

`method = "Predication"`

)

(see`Predication`

)If

`method="Predication"`

is used,`x`

will be taken as Predicate and`y`

will be taken as Argument of the phrase (see*Examples*)Circular Convolution (

`method = "CConv"`

)*p_i = ∑\limits_{j} u_j * v_{i-j}*,

where the subscripts of*v*are interpreted modulo*n*with*n =*`length(x)`

(=`length(y)`

)Dilation (

`method = "Dilation"`

)*p = (u*u)*v + (λ - 1)*(u*v)*u*,

with*(u*u)*being the dot product of*u*and*u*(and*(u*v)*being the dot product of*u*and*v*).

The `Add, Multiply,`

and `CConv`

methods are *symmetrical* composition methods,

i.e. `compose(x="word1",y="word2")`

will give the same results as `compose(x="word2",y="word1")`

On the other hand, `WeightAdd, Combined, Predication`

and `Dilation`

are *asymmetrical*, i.e. `compose(x="word1",y="word2")`

will give different results than `compose(x="word2",y="word1")`

The phrase vector as a numeric vector

Fritz G?nther

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

Mitchell, J., & Lapata, M. (2008). Vector-based Models of Semantic
Composition. In *Proceedings of ACL-08: HLT* (pp. 236-244).
Columbus, Ohio.

Mitchell, J., & Lapata, M. (2010). Composition in Distributional Models of Semantics.
*Cognitive Science, 34,* 1388-1429.

1 2 3 4 5 6 7 8 9 10 11 12 | ```
data(wonderland)
compose(x="mad",y="hatter",method="Add",tvectors=wonderland)
compose(x="mad",y="hatter",method="Combined",a=1,b=2,c=3,
tvectors=wonderland)
compose(x="mad",y="hatter",method="Predication",m=20,k=3,
tvectors=wonderland)
compose(x="mad",y="hatter",method="Dilation",lambda=3,
tvectors=wonderland)
``` |

codymarquart/LSAfun2 documentation built on May 13, 2019, 8:48 p.m.

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